Albano Moura, Author at Foxit

eSignature API: A Developer’s Guide to Adding Signing to Your App

Adding a signing step to your app involves more than it first appears. Authentication, document preparation, session handling, and completion tracking all need to work together. This guide walks through a full esignature API integration with Foxit eSign, from your first authenticated request to a signed, webhook-confirmed document.

Adding a signing step to an existing app sounds straightforward until you try to implement it. Getting a document signed is a simple idea, but the actual API surface, how authentication works, how you mark up a PDF, and how you learn that signing finished all take longer to figure out than they should. This guide walks a complete Foxit eSign API integration from the first authenticated request through to a webhook-confirmed, digitally signed document. Comfort with REST APIs and bearer tokens is enough to follow along.

What an eSignature API is and how signing workflows work

An eSignature API is a REST interface that owns the document-signing lifecycle, covering preparation, delivery, the signing session, and the audit trail. You supply the document and the signers, and the API handles field rendering, identity capture, signature application, and tamper-evident recordkeeping, so none of that infrastructure is yours to build.

The distinction that matters most for app developers is redirect-based versus embedded signing. Redirect-based signing sends the user to a hosted URL to sign and returns them afterwards, which means they leave your product mid-task. Embedded signing renders the session inside your own application, typically in an iframe, so the user never changes context. If signing sits in the middle of an onboarding or checkout flow, embedded keeps that flow intact.

Foxit eSign supports both. The lifecycle you implement runs through five stages, starting with OAuth 2.0 authentication, then PDF preparation with Text Tags, a POST to /esign/api/v1/folders/createfolder that defines signers and mints a session, the signer completing the embedded session, and a folder_executed webhook confirming the document is final.

The five stages this guide implements in order. Each one maps to a section below.

Prerequisites

Signing up for eSign API access is self-serve on the Foxit API Platform — no sales ticket and no waiting for an administrator. The platform provisions a trial eSign account for you and manages its credentials, so the whole setup is a short walkthrough:

Create and sign in to your Foxit API Platform account. You need an active Foxit API plan and a complete CAS profile — first name, last name, email address, and company name (a company address is required for eSign provisioning). Your eSign account is provisioned from those profile details, so complete them before you start.
Open the Dashboard and select Get started with eSign in the Dashboard header. That takes you to the eSign activation page.
Choose your document-storage region. The activation card preselects United States, with European Union and Canada as alternatives. Select Activate with [region] storage. Confirm the region before activating: once the remote account exists, the region is locked, and changing it later means submitting a case with Foxit Support.
Wait for provisioning to complete. You may see “Creating your eSign account” and then “Confirming your eSign account” — the second is a reliability check that reconciles ambiguous creation results, so let it finish instead of retrying activation.
Confirm eSign is ready. A successful activation displays “eSign is ready”, your eSign company number, and the selected region. The platform manages the API account and its credentials, and the same unified client_id/client_secret you use for PDF Services also authenticate eSign API, Document Generation, and Embed API — there is no separate eSign key pair to generate. If credential retrieval is still pending or failed, use Resume credentials or Retry credentials on the page; the first-call button stays disabled until credentials are ready.
(Optional but worth it) Run the sample request on the activation page. It uses your profile’s name and email as the first signing party, sends a Base64-encoded one-page contract, adds Signer Name, Today’s Date, Signature, and Date Signed fields, creates a draft with sending disabled, and returns an embedded sending session URL — a quick end-to-end check that everything is wired up. The button switches to Running and then reports “Sample draft created. The embedded sending session is ready.”

Two things to know before you build: your provisioned account is an eSign Business trial that lasts 30 days and starts in TEST mode, so every envelope carries a watermark. Moving the account to Production mode is a Sales/Operations step performed in Foxit Monitor, not something the API can do.

Beyond the account, the rest of the prerequisites are lightweight:

Python 3.8+ with pip and a venv, for the webhook handler later in this guide.
Flask and requests for the sample code.
curl for the token exchange, and ngrok or any tunnel that gives your local webhook endpoint a public HTTPS URL.
A code editor, VS Code with the Python extension being a reasonable default alongside PyCharm.
A tagged sample PDF, so you do not have to author one. This guide uses agreement-signable.pdf, which already carries Text Tags for a single signer.

Scaffold the workspace in one shot:

mkdir foxit-esign && cd foxit-esign
python3 -m venv .venv && source .venv/bin/activate
pip install flask requests
export ESIGN_HOST="https://na1.foxitesign.foxit.com"export ESIGN_CLIENT_ID="your_api_key"
export ESIGN_CLIENT_SECRET="your_api_secret"
export WEBHOOK_SECRET="your_webhook_secret"

Step 1: Authenticate with the Foxit eSign API

The platform provisions your eSign account and manages its credentials, and that single pair is shared across eSign API, PDF Services, Document Generation, and Embed API. No bearer token, no client_credentials grant, no expires_in to watch.

The quickest way to prove a credential pair works is a minimal folder creation — the same /esign/api/v1/folders/createfolder endpoint Step 3 explains field by field:

curl -X POST "$ESIGN_HOST/esign/api/v1/folders/createfolder" \
  -H "client_id: $ESIGN_CLIENT_ID" \
  -H "client_secret: $ESIGN_CLIENT_SECRET" \
  -H "Content-Type: application/json" \
  -d '{
    "folderName": "Auth check",
    "inputType": "url",
    "fileUrls": ["https://github.com/lucienchemaly/foxit-demo-templates/raw/main/esign/agreement-signable.pdf"],
    "fileNames": ["agreement.pdf"],
    "parties": [
      {
        "firstName": "Jane",
        "lastName": "Smith",
        "emailId": "[email protected]",
        "permission": "FILL_FIELDS_AND_SIGN",
        "sequence": 1
      }
    ],
    "processTextTags": false,
    "processAcroFields": false,
    "createEmbeddedSigningSession": false,
    "createEmbeddedSendingSession": true,
    "sendNow": false
  }'

A valid credential pair returns JSON with a folder object carrying folderId and folderStatus (DRAFT here, since sendNow is false), so the response doubles as your auth check — a rejected pair comes back as an error before any folder exists. Send the same two headers on every subsequent request. There is nothing to mint or refresh like an OAuth token; if the platform ever flags the stored credentials as stale, refresh them from the activation page with Resume credentials or Retry credentials. And because eSign shares the PDF Services credential pair, the two integrations are interchangeable — one pair of credentials covers both.

Step 2: Prepare a document and define signature fields with Text Tags

Foxit eSign reads field definitions out of the PDF itself at upload time. You embed them as Text Tags, plain-text strings placed where each field belongs, and the API converts them into interactive fields on ingest.

The syntax is ${fieldtype:party_number:required:field_name:width}, where y marks a field required and n marks it optional, the party number maps to a signer’s sequence, and width is expressed as underscores.

${signfield:1:y:____}                 # required signature, party 1
${datefield:1:y::____}                # required date, party 1
${i:1:______}                         # initials field, party 1
${t:1:y:Full_Name:__________}         # required text field, party 1, named "Full_Name"
${signfield:2:y:____}                 # required signature, party 2

Each tag names a type, either in full or by its short alias. The supported set covers signfield (s), initialfield (i), datefield (d), textfield (t), textboxfield (tb), checkboxfield (c), radiobuttonfield (rb), securedfield (sc), attachmentfield (a), imagefield (img), accept (ab), decline (db), payfield (pf), and formulafield (ff). Author them in lowercase to match the documented syntax.

Express width as underscores and never as a literal space, because a space stops the tag from being recognized. A tag written ${s:1: } renders in the signing UI as plain ${s:1: } text with no field attached, while ${signfield:1:y:____} becomes a real signature field. That failure is silent, so the create call still succeeds and you only notice when a signer has nothing to sign.

Two preparation details save support tickets later. Foxit eSign converts tags to fields but does not delete the tag text, so set the tag’s text color to match the page background if you do not want signers reading raw ${...} strings. And paste tags through a plain-text editor first, because smart-quote autocorrect in Word or Google Docs silently swaps straight ASCII characters for typographic ones and tag parsing then fails without an error.

If you would rather not tag a document by hand for a first run, agreement-signable.pdf is already prepared and hosted at a public URL you can pass straight to the next step.

Step 3: Send the document and mint an embedded session

One call to /esign/api/v1/folders/createfolder submits the document, defines the signers, and, when you ask for it, returns a ready-to-render signing URL. Foxit calls the signing container a folder rather than an envelope.

{
  "folderName": "Customer Agreement - Acme Corp",
  "fileUrls": ["https://github.com/lucienchemaly/foxit-demo-templates/raw/main/esign/agreement-signable.pdf"],
  "fileNames": ["agreement.pdf"],
  "parties": [
    {
      "firstName": "Jane",
      "lastName": "Smith",
      "emailId": "[email protected]",
      "permission": "FILL_FIELDS_AND_SIGN",
      "sequence": 1
    }
  ],
  "processTextTags": true,
  "createEmbeddedSigningSession": true,
  "embeddedSignersEmailIds": ["[email protected]"],
  "sendNow": false
}

In this body you point the API at the tagged PDF with fileUrls and give it a display name through fileNames, define the single signer in parties with firstName, lastName, emailId, the FILL_FIELDS_AND_SIGN permission and a signing sequence, then set processTextTags to true so the embedded tags become real fields. Asking for createEmbeddedSigningSession and naming the signer in embeddedSignersEmailIds returns a session URL in the same response, and sendNow set to false keeps Foxit from emailing an invitation, which is what you want while testing.

One nuance to expect here. sendNow: false on its own produces a DRAFT folder, but pairing it with createEmbeddedSigningSession returns folderStatus of SHARED, since the folder has to be live for the session URL to open. No email goes out either way, so the flag still suppresses the invitation, and the status you see just reflects that the document is now signable. To attach the file as bytes instead of a URL, send base64FileString as an array together with inputType set to "base64".

The response nests the folder identifier at folder.folderId and carries an embeddedSigningSessions array. Each entry holds emailIdOfSigner, the raw embeddedToken, and the renderable embeddedSessionURL, which follows this shape:

https://{HOST_NAME}/embedded/embeddedsign?eetid={URL-ENCODED-EMBEDDED-TOKEN}

Three behaviors are worth designing around before you ship. Omitting embeddedSignersEmailIds returns email id of embedded signer(s) not submitted, so always list embedded signers explicitly. Every party number used in a Text Tag needs a matching entry in parties, because a sendNow: true create still reports success while silently dropping the fields of a party that is not listed, which means a mandatory signature is never routed. And for a multi-party document where everyone signs in your app, createEmbeddedSigningSessionForAllParties set to true covers all recipients rather than naming them one by one.

To dispatch a draft later, POST to /api/folders/sendDraftFolder.

Folder state moves through DRAFT, SHARED, COMPLETED, and finally EXECUTED once the digital signature is applied. A run of this guide’s single-signer flow produced exactly that path, with the activity log labelling the creation event CREATED and then recording Envelope viewed, Jane Smith signed this folder at COMPLETED, and Document(s) successfully executed at EXECUTED. PARTIALLY SIGNED appears only when a folder has more than one party and some but not all of them have signed, so you will not see it on a single-signer document.

Step 4: Render the signing session in your app

Load the embeddedSessionURL in an iframe. The sandbox attribute needs a specific minimum set of permissions, and trimming it is a common way to break the signing UI with no visible error.

<iframe
  id="signing-session"
  src="PASTE_EMBEDDED_SESSION_URL_HERE"
  width="100%"
  height="780px"
  style="border: none;"
  sandbox="allow-scripts allow-same-origin allow-forms allow-popups allow-top-navigation"
></iframe>

In this markup the src receives the embeddedSessionURL from the createfolder response, and the five sandbox permissions are the minimum the signing UI needs. Removing allow-popups or allow-top-navigation breaks the flow in ways that surface no obvious error, so keep all five unless you have tested a reduced set end to end. Session URLs are short-lived, so generate one when the user is ready to sign rather than caching it, and request a fresh one per signer through /esign/api/v1/embedded/regenerateEmbeddedSigningSession when a session goes stale.

To check the flow before wiring it into your own UI, download the ready-to-run iFrame test page, open it in a browser, paste your embeddedSessionURL into the input, and load it. A correctly tagged document renders with active signing controls.

A real session opened from the embeddedSessionURL this guide’s request returns. All four tags in the sample became required fields, which is what the counter is reporting. The raw tag text still shows through each box, which is exactly why you color it to match the page background before shipping.

Step 5: Confirm completion with webhooks

Polling for completion wastes requests and adds latency. Register a webhook instead and Foxit eSign posts to your endpoint as each signing event happens.

Registration lives on the eSign portal’s API settings page at /consumer/consumerdetails, under Configure Webhooks, where you set the callback URL, a webhook secret, and the events you want. That page is visible only to the account owner, so an admin-level user will not find it. Your endpoint has to be reachable over public HTTPS.

The owner-only webhook settings. The event checkboxes control which callbacks reach your endpoint.

The events available are folder_sent, folder_viewed, folder_signed, folder_cancelled, folder_executed, folder_deleted, folder_completed, folder_assigned, and folder_access_code_failure. In practice folder_viewed, folder_signed, folder_completed, and folder_executed are the ones that fire on an API-dispatched folder.

The event to build on is folder_executed. folder_completed fires once every party has signed, but folder_executed fires after Foxit applies the digital signature and locks the audit trail, so it is the point at which a download gives you the final document.

Foxit signs every callback. It delivers the POST as <your-url>?signature=<base64>, where the signature is the base64 of an HMAC-SHA-256 over the raw request body keyed with your webhook secret. Verify it against the unparsed bytes, since re-serializing the JSON changes whitespace or key order and breaks the comparison.

import base64
import hashlib
import hmac
import os

from flask import Flask, request, jsonify

app = Flask(__name__)
WEBHOOK_SECRET = os.environ["WEBHOOK_SECRET"]


def verify_signature(raw_body: bytes, signature: str) -> bool:
    expected = base64.b64encode(
        hmac.new(WEBHOOK_SECRET.encode(), raw_body, hashlib.sha256).digest()
    ).decode()
    return hmac.compare_digest(expected, signature)


@app.route("/webhooks/esign", methods=["POST"])
def handle_esign_event():
    raw_body = request.get_data()
    if not verify_signature(raw_body, request.args.get("signature", "")):
        return jsonify({"error": "invalid signature"}), 403

    payload = request.get_json(silent=True) or {}
    event_name = payload.get("event_name")
    folder = payload.get("data", {}).get("folder", {})

    if event_name == "folder_executed":
        # The document is final here. Archive it, update your record, notify the user.
        app.logger.info("Signing finished for folder %s", folder.get("folderId"))

    return jsonify({"status": "received"}), 200

In this handler you read the unparsed body first, recompute the HMAC over those exact bytes with your webhook secret, and compare it against the signature query parameter using hmac.compare_digest so the check is not timing-dependent. A mismatch returns 403 before any business logic runs, which stops a spoofed POST to your public URL from triggging an archive. Only after the signature passes do you parse the JSON, read event_name, and branch on folder_executed to run downstream work, returning 200 so Foxit records the delivery as successful. A ready-to-run version of this receiver lives at webhook_receiver.py in the demo repo.

Test the whole path against a draft. Create the folder with sendNow set to false, dispatch it, sign in the embedded session, and watch the events arrive. Once the signer finishes, the session redirects to a result URL carrying event=signing_success, and the document reaches EXECUTED within a few seconds.

The session once every field is filled. The counter reads zero and Finish activates, which is the state that produces folder_completed and then folder_executed.

Step 6: Retrieve the executed document and its audit trail

With folder_executed in hand, pull the final PDF. The download takes the folder id as a query parameter.

curl -o executed.pdf \
  "$ESIGN_HOST/api/folders/download?folderId=35117696" \
  -H "Authorization: Bearer $ACCESS_TOKEN"

The response streams the executed PDF, which arrives with a content type of application/octet-stream rather than application/pdf, so write the bytes to a file rather than sniffing the header. The returned document carries the filled field values and the signature certificate, so a text extraction of it contains the signer’s typed name, the date, and the per-signer Signer ID recorded on the certificate page.

For the audit trail itself, GET /api/folders/viewActivityHistory?folderId={id} returns a details object holding the folder metadata plus an activities array, where each entry carries an activity description and the folderStatus at that moment. That endpoint is GET-only and only returns data once the folder has been shared, so a pure DRAFT folder reports nothing useful.

The signature certificate attached to a document once folder_executed has fired. Each signer’s adopted signature sits beside the identity record Foxit captured, which is the tamper-evident audit trail you are archiving alongside the PDF.

Common mistakes

Dropping the /api/ prefix : every eSign path sits under /api/, so it is /api/folders/createfolder, not /folders/createfolder.
snake_case request fields : the body is camelCase. folderName, fileUrls, emailId, and sendNow work, while folder_name, document_url, email, and send_now do not.
Omitting processTextTags : without it the tags stay inert text, the signer sees raw ${...} strings, and they can finish without signing anything.
A tag party with no matching parties entry : the create returns success and that party’s fields disappear silently, so their signature is never collected.
Skipping signature verification : a public webhook URL that acts on any POST is a spoofing target. Verify the HMAC before you touch the payload.
Archiving on folder_completed : that fires before the digital signature is applied. Wait for folder_executed.
Caching an embeddedSessionURL : sessions expire. Mint one when the signer is ready, and regenerate when needed.
Trimming the iframe sandbox list : removing allow-popups or allow-top-navigation breaks signing with no error message.
Smart quotes or a space inside a tag : both stop tag recognition. Use straight ASCII and underscores.
Reusing PDF Services credentials : eSign has its own portal, host, and key pair.

eSignature API FAQ

What is an eSignature API?

A REST interface that handles the document-signing lifecycle, covering preparation, delivery, the signing session, and the audit trail, so your app makes calls rather than building signing infrastructure.

What is embedded signing and why does it improve the user experience?

Embedded signing renders the session inside your own application instead of redirecting to a hosted page, so the signer finishes without leaving your product. That matters most when signing sits inside a flow you do not want to interrupt, like onboarding or checkout.

How do Text Tags relate to the parties in the API call?

The party number in a tag maps to a signer’s sequence in the parties array, so ${s:1: } is signed by the party with sequence: 1. Keeping those aligned is the difference between fields routing correctly and vanishing silently.

What is the difference between folder_completed and folder_executed?

folder_completed fires when all parties have signed. folder_executed fires after Foxit applies the digital signature and locks the audit trail, which is why downstream archiving should trigger on folder_executed.

How do I verify a webhook actually came from Foxit?

Recompute a base64 HMAC-SHA-256 of the raw request body using your webhook secret and compare it with the signature query parameter. Verify against raw bytes, never re-serialized JSON.

Can one folder hold several documents?

Yes. Pass additional entries in fileUrls with matching fileNames. Each document carries its own Text Tags, and party assignments stay consistent across the folder.

Do I need a paid plan to build this?

No. The free tier gives you credentials and lets you run the full flow, and no credit card is required to create the account.

Can I review a document before it reaches signers?

Yes. Create it with sendNow set to false for a DRAFT folder, inspect it in the eSign dashboard, then dispatch with /api/folders/sendDraftFolder.

Wrapping up

That is the full path for an eSignature API integration. Authenticate with the client_credentials grant, prepare a PDF with Text Tags, create the folder with processTextTags and an embedded session, render the returned embeddedSessionURL in an iframe, and act on a signature-verified folder_executed webhook.

The same shape extends to multi-signer approval chains, CRM-triggered signing when a deal closes, and template-based documents where fields arrive pre-filled from your own data. Those build on the pieces already in place rather than replacing them.

Ready to build? Create a free account (no credit card required) at account.foxit.com/site/sign-up, generate your API Key and Secret from the API tab, and run the token call above against agreement-signable.pdf to see a session URL come back.

Build a CRM-Triggered PDF Generation and eSign Workflow in Power Automate with Foxit’s REST APIs

This guide shows how to trigger a Word-to-PDF contract from a closed CRM deal, route it for signature through Foxit’s eSign API, and archive the signed copy automatically, using nothing but HTTP actions and a webhook.

Most Power Automate document tutorials stop at a SharePoint file move or an AI Builder extraction, and the ones that touch signatures assume a native connector that does not exist for a headless, API-first pipeline. The gap is the full chain, where a CRM deal closes, a contract is generated from a Word template, the PDF is routed for signature, and the signed copy is archived, with no manual export and no polling. This article builds that pipeline in Power Automate using the HTTP action to call Foxit’s REST endpoints directly, which is the same pattern that carries over to n8n, Zapier, or any orchestrator that can make an HTTP request.

Foxit exposes two REST APIs that chain cleanly for this. The Document Generation API takes a base64-encoded Word template plus a JSON payload and returns a base64 PDF, and the eSign API handles the signing lifecycle behind an OAuth2 token. The base64 PDF from generation drops straight into the eSign upload call, so the handoff stays inside one flow with no SDK to install and no desktop agent. This Power Automate Foxit API integration walks the two hosts and their two auth models, the document generation call, the send-for-signature call with embedded signature fields, and a second flow that receives Foxit’s webhook and archives the executed document.

Prerequisites

Power Automate runs in the browser, so there is no local runtime to install. What you need are the right accounts and one sample file.

A Power Automate account with the HTTP action : the HTTP action is a premium connector, so you need a per-user or per-flow premium license. This is the one paid dependency in the tutorial. On the free Microsoft 365 tier you will hit a wall at the first HTTP action, so confirm the plan before you start.
A Foxit Developer account : create one at account.foxit.com/site/sign-up and activate the free Developer plan, which includes 500 credits per year with no credit card. From the APIs Dashboard, copy the Document Generation Client ID and Secret, and separately the eSign Client ID and Secret. These are two different credential pairs for two different APIs.
A CRM that can trigger a flow : this article uses the Salesforce connector as the example. Any CRM with a Power Automate connector, or any system that can POST to a webhook URL, works the same way.
The sample contract template : download contract_signing.docx so you do not have to author one. It already carries both Document Generation merge tags and eSign signature tags, which is what makes the two-API handoff work.
A REST client : Postman or curl, to test each Foxit call in isolation before wiring it into a flow.

Store both Foxit credential pairs in the Power Automate secure store or as environment variables in your solution, never pasted as literals into an action, so they do not travel in exported flow definitions.

The APIs Dashboard is where you retrieve the Client ID and Secret. Document Generation and eSign each have their own pair.

How the Power Automate Foxit API Integration Works: Two APIs, Two Hosts, Two Flows

The pipeline has four stages. A CRM Closed Won event triggers document generation, the generated PDF is sent for signature, and the executed document is archived once every party has signed.

Salesforce: Opportunity → Closed Won
        │
        ▼
HTTP: POST GenerateDocumentBase64   (na1.fusion.foxit.com)   → base64 PDF
        │
        ▼
HTTP: POST createfolder             (na1.foxitesign.foxit.com) → folderId, email sent
        │
   … signer signs (async) …
        ▼
Flow 2: When a HTTP request is received  <- Foxit webhook (folder_executed)
        │
        ▼
HTTP: GET download → OneDrive: Create file

Power Automate owns orchestration and control flow. Foxit owns document rendering and the signature lifecycle. The single most common mistake in this integration is treating the two Foxit products as one, so keep them separate from the start. Document Generation runs on https://na1.fusion.foxit.com and authenticates with lowercase client_id and client_secret request headers. eSign runs on https://na1.foxitesign.foxit.com and authenticates with an OAuth 2.0 bearer token obtained from its own credential pair. They do not share credentials or a portal.

The work also splits into two flows for a reason. Generation and sending are synchronous, so they belong in one flow that runs when the deal closes. Signing completes minutes or days later, so a second flow triggered by Foxit’s webhook handles the archive step. That separation is what removes any polling from the design.

Here is the main flow built in the Power Automate designer, with the four HTTP actions chained after the trigger.

The four HTTP actions in order. This build uses a manual trigger so the flow runs on demand while you test; in production the Salesforce trigger from Step 1 takes its place as the entry point, and nothing downstream changes.

Step 1: CRM Trigger, Firing the Flow on a Closed Deal

Create an automated cloud flow and choose the Salesforce trigger for a created or modified record, pointing it at the Opportunity object. Add a condition so the flow only proceeds when the Stage equals Closed Won, which keeps every mid-pipeline edit from generating a contract.

Map the CRM fields the contract needs. For the sample template, that is the client name, the contract date, the deal value, and the signer’s name and email. Read them from the trigger output with expressions like triggerOutputs()?['body/Account_Name'] and store each in a variable or reference it inline, so the next two steps can assemble their payloads cleanly.

This step is swappable. Any CRM with a Power Automate connector, or any system that can POST JSON to a Power Automate HTTP-request trigger, drops in here without touching the Foxit calls that follow. If you use HubSpot or Dynamics 365, only the trigger and field paths change, so the rest of this tutorial stays identical.

Step 2: Generate the Contract PDF with GenerateDocumentBase64

The contract_signing.docx template drives this step. It contains Document Generation merge tags for the scalar fields and a table loop for line items, using Foxit’s {{ }} syntax:

{{clientName}}
{{contractDate \@ MM/dd/yyyy}}
{{dealValue \# "$#,##0.00"}}

{{TableStart:lineItems}} {{description}}   {{amount}} {{TableEnd:lineItems}}

The \@ switch formats a date and the \# switch formats a currency value, so you can pass a raw ISO date and a plain number and let the template render them. The {{TableStart:lineItems}} and {{TableEnd:lineItems}} tokens sit in a single Word table row and repeat that row for each object in the lineItems array.

Before the flow can send the template, it needs the file as a base64 string. The build here gets it with an HTTP GET action named Get template, pointed at the raw contract_signing.docx URL, and base64-encodes the response with the base64() expression. For a template you maintain yourself, store it in OneDrive or SharePoint and use a Get file content action instead of the GET. Then add a second HTTP action named Generate PDF, set to POST https://na1.fusion.foxit.com/document-generation/api/GenerateDocumentBase64 with client_id and client_secret headers and this JSON body:

{
  "base64FileString": "@{base64(body('Get_template'))}",
  "documentValues": {
    "clientName": "@{variables('clientName')}",
    "contractDate": "2026-07-17",
    "dealValue": 48500,
    "lineItems": [
      { "description": "Platform license (annual)", "amount": "$36,000.00" },
      { "description": "Onboarding and training", "amount": "$12,500.00" }
    ]
  },
  "outputFormat": "pdf"
}

In this code, you send the base64-encoded template as base64FileString, pass the CRM-sourced fields as documentValues whose keys match the template tags exactly, and request a PDF with outputFormat set to the lowercase "pdf". The keys clientName, dealValue, and the lineItems array with its description and amount fields have to match the tag names in the Word file, since a mismatch leaves the tag unrendered rather than raising an error. The call is synchronous and returns HTTP 200 with a JSON response containing message, fileExtension, and base64FileString, where base64FileString is the rendered PDF as a base64 string.

The call is synchronous, so there is no task to poll and no status to check, and the generated contract is available immediately. Reference the rendered PDF in the next step directly with the expression body('Generate_PDF')?['base64FileString'], or add a Parse JSON action first if you prefer typed outputs. When you need the raw bytes rather than the string, for archiving or a file action, convert with the base64ToBinary() expression, one of the Workflow Definition Language conversion functions.

One limit to plan for is the upload size. Document Generation rejects .docx payloads larger than 4 MB after base64 encoding, which is roughly a 3 MB raw file, and the limit is not surfaced in a friendly error. If you hit it, compress images through Word’s Picture Format tools, drop embedded fonts and OLE objects, and split oversized templates. The sample here is about 37 KB, so first runs stay well clear of the cap. For template authoring detail and common payload errors, Foxit’s Document Generation API quickstart is the reference.

The generated contract. The signature and date fields at the bottom come from the eSign Text Tags embedded in the same template, ready for Step 3.

Step 3: Send for Signature with OAuth2 and createfolder

The eSign API needs a bearer token first. Add an HTTP action that POSTs to https://na1.foxitesign.foxit.com/api/oauth2/access_token with content type application/x-www-form-urlencoded and this body:

grant_type=client_credentials&client_id=YOUR_ESIGN_CLIENT_ID&client_secret=YOUR_ESIGN_CLIENT_SECRET&scope=read-write

Name this action Get eSign token. Its JSON response carries access_token, token_type set to bearer, expires_in, and instance_url, and you reference the token in the next call as body('Get_eSign_token')?['access_token']. This is the client-credentials grant, which fits a server-to-server flow where no human is present to log in.

The signature fields are already defined in the template. contract_signing.docx carries two eSign Text Tags, ${signfield:1:y} and ${datefield:1:y}, which follow the ${fieldtype:party:mandatory} syntax. Here both are mandatory fields assigned to party 1, the client who signs. Because the tags live in the Word file, the PDF that Document Generation produced in Step 2 already has a signature and date field in place, so there is no manual field placement after generation. Keep two rules in mind when you author your own tags. Replace any space inside a tag with an underscore, since a literal space breaks tag recognition, and set the tag text color to match the document background so the tokens do not show in the final PDF.

Now add the send action, an HTTP action named Create signing folder, set to POST https://na1.foxitesign.foxit.com/api/folders/createfolder with an Authorization: Bearer @{body('Get_eSign_token')?['access_token']} header and this body:

{
  "folderName": "Acme Corp Contract",
  "inputType": "base64",
  "base64FileString": ["@{body('Generate_PDF')?['base64FileString']}"],
  "fileNames": ["contract_signing.pdf"],
  "parties": [
    {
      "firstName": "Jordan",
      "lastName": "Lee",
      "emailId": "[email protected]",
      "permission": "FILL_FIELDS_AND_SIGN",
      "sequence": 1
    }
  ],
  "processTextTags": true,
  "sendNow": true
}

In this code, you attach the Step 2 PDF by passing it as the single element of the base64FileString array together with inputType set to "base64", which is the pairing the API requires for base64 uploads. The parties array names the signer with firstName, lastName, emailId, and a permission of FILL_FIELDS_AND_SIGN, and its sequence of 1 matches the party number in the ${signfield:1:y} tag. Setting processTextTags to true is what converts those embedded tags into real, interactive fields, and sendNow set to true dispatches the signing invitation immediately. The response returns result as success and nests the identifier at folder.folderId, which you store for the archive flow. Foxit calls this container a folder rather than an envelope.

The Create signing folder action. The access_token and base64FileString chips are dynamic references to the two prior HTTP actions, so the eSign token and the generated PDF flow straight into this call with no copy-paste.

Two behaviors are worth handling before you ship. Every party number referenced by a Text Tag must have a matching entry in the parties array, because if a tag points at a party that is not listed, a sendNow: true create still returns success but silently drops that party’s fields, so their signature is never routed. If you need a human to approve the contract before it leaves, set sendNow to false to create a draft without emailing anyone, then dispatch it later with POST https://na1.foxitesign.foxit.com/api/folders/sendDraftFolder.

What the recipient sees after createfolder sends the invitation. The signature field is the one defined by the ${signfield:1:y} tag.

Step 4: Receive the Webhook and Archive the Signed Document

Create a second automated flow using the When a HTTP request is received trigger. Saving the flow generates a callback URL. Register that URL as the webhook endpoint on the eSign portal’s API settings page, which is owner-only, and select the signing events you want delivered.

Archive on the right event. The folder status moves through DRAFT, then SHARED, then PARTIALLY SIGNED, then COMPLETED, then EXECUTED. Trigger the archive on folder_executed, not folder_completed. The folder_completed event fires when all signatures are in but before the digital signature has been applied to the PDF, whereas folder_executed guarantees the file you download is the final, digitally signed document.

Verify each callback before acting on it. Foxit delivers every webhook as POST <your-url>?signature=<base64>, where the signature is the base64 of an HMAC-SHA-256 of the raw request body keyed with your webhook secret. Power Automate’s expression language has no native HMAC function, so there are two practical paths. The stronger one calls a small Azure Function or an Office Script that recomputes the HMAC over the raw body and returns a match boolean, which the flow checks in a Condition. The lighter one restricts the trigger to your tenant and treats the webhook secret as a shared value checked in a Condition, which is simpler but weaker. Choose based on how exposed the endpoint is.

Once a callback is verified and the event is folder_executed, parse folderId from the payload and download the signed file. Add an HTTP action with the bearer token set to GET https://na1.foxitesign.foxit.com/api/folders/download?folderId=@{triggerBody()?['folderId']}, which returns the executed PDF as application/pdf. Pass the response body to the OneDrive for Business Create file action, naming the destination folder by deal name or date so contracts stay retrievable.

The owner-only webhook settings, where you paste the Power Automate callback URL and pick the events to receive.

If you cannot expose a public endpoint, poll instead. GET https://na1.foxitesign.foxit.com/api/folders/viewActivityHistory?folderId={id} returns the audit trail, with actions such as Created, Invitation Sent, Opened, Viewed, Signed, and Folder Executed. This endpoint is GET-only and only returns data once the folder has been shared or sent, so run it on a schedule from a separate flow.

Common Mistakes

Most failures in this pipeline come from a small set of recurring errors. Check these first when something does not work.

Using one credential pair or one token for both APIs : Document Generation uses client_id and client_secret headers on na1.fusion.foxit.com, while eSign uses a bearer token on na1.foxitesign.foxit.com. They are separate.
Sending the eSign PDF without inputType : the base64 upload needs inputType set to "base64" alongside the base64FileString array, or the API returns fileUrls or base64FileString cannot be empty.
Omitting processTextTags : without processTextTags set to true, the tags stay as inert text and the signer can finish without signing.
A tag party number with no matching party : if ${signfield:2:y} appears but the parties array has no party 2, the send succeeds and that party’s fields vanish silently.
Missing a party email field : each party needs emailId, not email. The wrong key returns email id of party cannot be empty.
Archiving on folder_completed : download on folder_executed instead, or you may pull a PDF before the digital signature is applied.
A stray space or smart quote in a tag : a literal space inside ${...} or a curly quote from Word autocorrect breaks tag recognition. Use straight quotes and underscores.

API Workflow Automation FAQ

Does this work with n8n or Zapier instead of Power Automate?

Yes. Any platform that can make HTTP requests and receive a webhook works, since the Foxit calls are identical. Only the orchestration layer changes.

Do I need a paid plan to test the Foxit side?

No. The free Developer plan gives 500 credits per year with instant activation and no credit card. The paid dependency here is the Power Automate premium license for the HTTP action.

Are Document Generation and eSign on the same credentials?

No. Each API has its own Client ID and Secret, so store two credential pairs and use each on its own host.

Can I skip generation and send an existing PDF to eSign?

Yes. The createfolder call accepts a base64 PDF directly, or a public file URL through fileUrls and fileNames, so the generation step is optional if you already have the document.

How do I add a second signer?

Add party-2 Text Tags to the template, such as ${signfield:2:y}, and a matching party-2 entry to the parties array. Keep the party numbers in the tags and the array aligned.

Next Step

The fastest way to confirm the pieces before building the flow is to run one call by hand. Create your free Foxit Developer account, pull your Document Generation and eSign Client IDs and Secrets from the APIs Dashboard, and run a single GenerateDocumentBase64 call against contract_signing.docx in a REST client. Once it returns a base64 PDF, you know the credentials and payload are right, and the rest of the Power Automate Foxit API integration is just wiring the same calls into actions. Create your free account to get started.

Build a CRM-Triggered Document Pipeline with Foxit APIs in n8n, with a Vercel Workflows Alternative

This tutorial shows how to wire a CRM webhook, the Foxit Document Generation API, and the Foxit eSign API into one durable pipeline, without manual copying of data between tools. You’ll build it twice: once visually in n8n, and once as a resumable serverless function in Vercel Workflows.

Most document automation tutorials stop at the happy path. Generate a PDF, send it for signature, done. What they skip is the plumbing, which is where a real pipeline lives or dies. How does a CRM event actually hand off to a document API? How do you pass a signed document downstream without a polling loop? What happens when one step fails halfway through and you do not want to re-run the steps that already succeeded?

If you have tried to stitch a multi-step document workflow across a CRM, a generator, and an eSign service, you know exactly where the seams are. The deal data lives in the CRM, the template lives somewhere else, the signature lives in a third system, and a person ends up copying state between them.

This tutorial closes those seams. A CRM deal-closed event fires a webhook, a workflow renders a contract from a Word template, routes it for signature, waits for completion, and archives the signed file, with no human in the loop. You will build it first in n8n, a source-available workflow tool, and then rebuild the same pipeline as a durable function with Vercel Workflows. Both use the Foxit Document Generation API and the Foxit eSign API with real endpoints and real request shapes.

Durability is the theme. A production pipeline must survive a step failure, retry without repeating completed work, and hold state across an asynchronous signing wait that can last minutes or days.

Architecture Overview: Two Ways to Build the Same Pipeline

The pipeline is four stages, and each hands its output directly to the next.

Trigger. A CRM webhook (a HubSpot deal-stage change in this example) delivers the deal data.
Generate. The workflow renders a contract PDF from a Word template through Document Generation, a synchronous REST call with no SDK to install.
Sign. The rendered PDF goes straight to the eSign API, which creates a signing folder and routes it to the signer.
Archive. When signing completes, the workflow downloads the executed PDF and writes it to storage.

In n8n, that maps to a Webhook node, an HTTP Request node for generation, an HTTP Request node for signing, a second Webhook node that waits for the eSign completion callback, and a final archive step.

The core chain in the local n8n editor. Each stage is a plain HTTP Request node, and the base64 PDF from the generation node flows straight into the eSign create-folder node.

The same pipeline can be written as code with Vercel Workflows, where the whole flow is one durable function, each Foxit call is a retrying step, and the eSign wait is a hook that resumes when the completion webhook arrives. Reach for n8n when you want visual orchestration and fast prototyping, and for Vercel Workflows when you want code-native durability and already run on Vercel. Section 7 builds that version.

One detail shapes every call. The two APIs live on two hosts and authenticate differently. Document Generation runs on https://na1.fusion.foxit.com and takes client_id and client_secret request headers. eSign runs on https://na1.foxitesign.foxit.com and takes an OAuth2 bearer token obtained from /api/oauth2/access_token.

Step 1: Credentials and Template Prep

The whole build runs on free infrastructure. Run n8n as the self-hosted Community Edition in Docker, and use Foxit’s free Developer plan. There is no n8n Cloud plan and no paid Foxit tier involved.

Register a Foxit account at account.foxit.com/site/sign-up, verify your email, and activate the free Developer plan. From the APIs Dashboard, copy your Document Generation Client ID and Client Secret. The eSign API is provisioned separately, so once eSign is active on your account, retrieve its API Key and API Secret as a distinct pair. You end up with two credential sets, and they are not interchangeable.

Store the Document Generation pair once in n8n’s credential store rather than pasting keys into nodes. Because Foxit needs two custom headers, use the Custom Auth credential type, which is the same type Foxit’s published template uses. Create a credential with this JSON:

{
  "headers": {
    "client_id": "YOUR_FOXIT_CLIENT_ID",
    "client_secret": "YOUR_FOXIT_CLIENT_SECRET"
  }
}

The Custom Auth credential holds both Foxit headers in one place, so your keys never appear in a node field or an exported workflow.

Now the template. Because the goal is a signing-ready contract, one Word file carries two families of tags. Document Generation merge tags use double braces for data, and eSign Text Tags use dollar-brace syntax for signature fields. Download the ready-to-use sample, contract_signing.docx. It carries {{clientName}}, {{dealValue \# "$#,##0.00"}}, {{contractDate \@ MM/dd/yyyy}}, a {{TableStart:lineItems}} / {{TableEnd:lineItems}} loop for line items, and the eSign Text Tags ${signfield:1:y} and ${datefield:1:y}. The Text Tag format is ${fieldtype:party:mandatory}, so ${signfield:1:y} is a required signature for party 1. Keep the raw file under about 3 MB, for the reason covered in Step 2.

Step 2: CRM Webhook to DocGen, Generating the Contract

Start the workflow with a Webhook node, which is how a CRM will call your pipeline when a deal closes. Set the method to POST and give it a path such as deal-closed. n8n gives the node a Test URL for building and a Production URL for live traffic.

The Webhook node’s Test URL. Click “Listen for test event” to capture a sample request while building.

Because a local build has no real CRM pointed at it, fire the webhook yourself. Click Listen for test event, copy the Test URL, and send a sample deal payload with cURL:

curl -X POST "http://localhost:5678/webhook-test/deal-closed" \
  -H "Content-Type: application/json" \
  -d '{ "clientName": "Acme Robotics", "dealValue": 48500, "contractDate": "2026-07-02" }'

In this request, you POST a small JSON object standing in for the CRM’s deal-closed payload. The Webhook node captures it and its fields become available to later nodes as {{ $json.body.clientName }}. In production, register the node’s Production URL in your CRM’s webhook settings, and expose your local instance with a tunnel such as ngrok if you are testing before deploying.

Add an HTTP Request node for generation. Set the method to POST, the URL to https://na1.fusion.foxit.com/document-generation/api/GenerateDocumentBase64, attach the Custom Auth credential, turn on Send Body, choose JSON, and send:

{
  "base64FileString": "<base64-encoded contract_signing.docx>",
  "documentValues": {
    "clientName": "{{ $json.body.clientName }}",
    "dealValue": "{{ $json.body.dealValue }}",
    "contractDate": "{{ $json.body.contractDate }}",
    "lineItems": [
      { "description": "Platform license (annual)", "amount": "$36,000.00" },
      { "description": "Premium support", "amount": "$5,000.00" }
    ]
  },
  "outputFormat": "pdf"
}

The HTTP Request config panel. Set the method and URL, attach the credential, and turn on Send Body for the JSON payload.

In this body, base64FileString is the template encoded as base64, documentValues is a flat object whose keys match the template tags exactly and whose values come from the webhook payload, and outputFormat is the lowercase "pdf". The keys must match the tag names character for character, because a mismatch does not raise an error. The call returns HTTP 200 and that field simply renders blank, so confirm names with POST /document-generation/api/AnalyzeDocumentBase64 if a field comes back empty. One more limit to plan for, since it surfaces as a bare HTTP 500 rather than a friendly message. Document Generation rejects a .docx payload larger than 4 MB after base64 encoding, which is roughly a 3 MB raw file, so compress images and drop embedded fonts if the template is heavy.

The endpoint is synchronous. The response carries message, fileExtension, and base64FileString, where the last holds the rendered PDF as base64. There is no job id and no polling, which keeps the graph linear. The generated contract has the data merged in and the Text Tags still present in the text, ready for signing.

The generated PDF. The merge tags are filled and the ${signfield:1:y} and ${datefield:1:y} Text Tags survive into the output, where eSign will convert them into fields.

Step 3: Routing the PDF into eSign

The eSign leg starts by turning your eSign credentials into a bearer token. Add an HTTP Request node that POSTs to https://na1.foxitesign.foxit.com/api/oauth2/access_token, with the body sent as Form Urlencoded and four fields, grant_type set to client_credentials, client_id, client_secret, and scope set to read-write. The response is JSON with access_token, token_type (the string bearer), expires_in, and instance_url. This is a standard OAuth2 client-credentials grant defined in RFC 6749. Cache the token against expires_in and refresh before it lapses rather than minting one per run.

The token node uses a Form URL Encoded body with the four OAuth fields. Click Execute step to confirm it returns a token before wiring the rest.

A successful token call. The green check and the returned access_token confirm the credentials and endpoint are correct.

Now add the send-for-signature node. POST to https://na1.foxitesign.foxit.com/api/folders/createfolder with an Authorization: Bearer <access_token> header and this body:

{
  "folderName": "Contract - {{ $('Webhook').item.json.body.clientName }}",
  "inputType": "base64",
  "base64FileString": ["{{ $('Generate PDF').item.json.base64FileString }}"],
  "fileNames": ["contract.pdf"],
  "processTextTags": true,
  "sendNow": true,
  "parties": [
    {
      "firstName": "Alex",
      "lastName": "Rivera",
      "emailId": "[email protected]",
      "permission": "FILL_FIELDS_AND_SIGN",
      "sequence": 1,
      "workflowSequence": 1
    }
  ]
}

The create-folder node. The Authorization header value Bearer {{ $json.access_token }} pulls the token from the previous node.

In this call, inputType is "base64" and base64FileString is an array holding the PDF from Step 2, which is the direct handoff between the two APIs. processTextTags: true converts the embedded Text Tags into real fields, and sendNow: true dispatches the folder in the same request. The response nests the identifier at folder.folderId, which you keep for the completion step. One rule fails silently, so check it. Every party number used in a Text Tag must have a matching entry in parties, or a sendNow: true call returns success while dropping that party’s fields. If you prefer a review gate, set sendNow: false and dispatch later with POST /api/folders/sendDraftFolder.

What the signer receives, from a real run of this exact pipeline. The ${signfield:1:y} tag in the template has become an interactive signature field, which confirms processTextTags did its job on the generated contract.

Step 4: eSign Completion Webhook and Archive

Register your callback URL in the eSign portal’s API settings page, under the Configure Webhooks section. This page is visible to the account owner once API access is active, so a non-owner login will not see it. Provide the HTTPS callback URL, a Webhook Secret, and the events you want delivered.

Archive at the right moment by understanding the lifecycle. A folder moves through DRAFT, then SHARED, then PARTIALLY SIGNED, then COMPLETED when all signatures are collected, then EXECUTED a few seconds later once the digital signature is applied. Hook folder_executed, not folder_completed, so the file you store is the finalized, digitally signed PDF.

Add a second Webhook node to receive the callback. Each callback POSTs a JSON body with event_name, event_date in Unix milliseconds, and data, where data.folder carries folderId, folderStatus, folderDocumentIds, and documentsList. Verify authenticity against the HMAC-SHA-256 digest Foxit computes over the raw request body with your Webhook Secret and appends to the callback URL as a signature query parameter. Compare against the raw body bytes, not a re-serialized payload.

On completion, download the executed document and archive it. A GET to https://na1.foxitesign.foxit.com/api/folders/download?folderId={id} with the bearer token returns the signed PDF as application/pdf. Route that binary to a storage node such as Google Drive, an S3 bucket, or an internal file-system node, then fire any downstream update.

Not every send completes, so handle the abandoned-signer path. If the completion webhook never fires, use an n8n Wait node with a timeout, or poll GET /api/folders/viewActivityHistory?folderId={id} (GET only, and it responds once the folder is shared) to read the audit trail, then branch to a follow-up rather than hanging.

The Vercel Workflows Alternative

If your stack already runs on Vercel, you can build the same pipeline as a durable function instead of a visual graph. Vercel Workflows is built on the open-source Workflow SDK. Scaffold a Next.js app, add the SDK, and wrap the config so the build compiles your workflow functions into durable routes:

npm create next-app@latest foxit-vercel-workflow
cd foxit-vercel-workflow
npm i workflow

// next.config.ts
import { withWorkflow } from "workflow/next";
import type { NextConfig } from "next";

const nextConfig: NextConfig = {};

export default withWorkflow(nextConfig);

A CRM would kick off a run by POSTing to an API route, which starts the workflow with start() and returns immediately while the durable function runs in the background:

// app/api/trigger/route.ts
import { NextResponse } from "next/server";
import { start } from "workflow/api";
import { contractWorkflow, type Deal } from "@/workflows/contract";

export async function POST(req: Request) {
  const deal = (await req.json()) as Deal;
  await start(contractWorkflow, [deal]);
  return NextResponse.json({ started: true });
}

The orchestration function carries the 'use workflow' directive, which makes it resumable and able to survive deploys and crashes through deterministic replay. It generates the contract, sends it for signature, then awaits a hook keyed by the folderId until the signing completes:

// workflows/contract.ts
import { signatureHook } from "./hooks";

export async function contractWorkflow(deal: Deal) {
  "use workflow";

  const pdfBase64 = await generateContract(deal);
  const folderId = await sendForSignature(pdfBase64, deal);

  // Pause here, consuming no compute, until the eSign webhook resumes it.
  const completion = await signatureHook.create({ token: String(folderId) });

  const archivedBytes = await archiveSigned(folderId);
  return { folderId, event: completion.event_name, archivedBytes };
}

Each Foxit call becomes a step. A function with the 'use step' directive runs a unit of durable work and gets built-in retries on transient failures like network errors, so a flaky call is retried without re-running the rest of the pipeline.

// app/steps/generate-contract.ts
async function generateContract(deal: Deal) {
  'use step';

  const res = await fetch(
    'https://na1.fusion.foxit.com/document-generation/api/GenerateDocumentBase64',
    {
      method: 'POST',
      headers: {
        client_id: process.env.FOXIT_DOCGEN_CLIENT_ID!,
        client_secret: process.env.FOXIT_DOCGEN_CLIENT_SECRET!,
        'Content-Type': 'application/json',
      },
      body: JSON.stringify({
        base64FileString: TEMPLATE_B64,
        documentValues: deal,
        outputFormat: 'pdf',
      }),
    },
  );
  const { base64FileString } = await res.json();
  return base64FileString;
}

The eSign wait is a hook, not a poll. Define a hook, create it keyed by the folderId, and resume it from an API route when Foxit POSTs the completion webhook. The workflow pauses without consuming compute and resumes exactly where it left off.

// workflows/hooks.ts
import { defineHook } from "workflow";

export type FoxitCompletion = {
  event_name: string;
  data: { folder: { folderId: number; folderStatus: string } };
};

export const signatureHook = defineHook<FoxitCompletion>();

// app/api/foxit-webhook/route.ts
import { signatureHook } from "@/workflows/hooks";

export async function POST(req: Request) {
  const payload = await req.json();
  const folderId = payload?.data?.folder?.folderId;
  // Resume only on the terminal event, so earlier lifecycle events
  // (viewed, signed, completed) do not consume the single-use hook.
  if (folderId && payload?.event_name === "folder_executed") {
    await signatureHook.resume(String(folderId), payload);
  }
  return new Response("OK");
}

In this code, the workflow calls two steps and then waits on signatureHook. When Foxit’s folder_executed webhook hits /api/foxit-webhook, the route calls hook.resume with the folderId as the key, which wakes the paused workflow and hands it the payload so it can archive the signed document. The event_name check matters, because the same account webhook also delivers folder_viewed, folder_signed, and folder_completed, and any of those would otherwise consume the single-use hook early. Use sleep() from the workflow package for a timeout fallback if the signer never acts. The credential and endpoint facts are identical to the n8n version, since only the orchestration layer changed. The Workflow Concepts page documents the directives, sleep, and hooks in full, and the full runnable project is in the demo repo.

Deployed to Vercel and triggered with a sample deal, the run shows up under Observability, where you can watch runs pause and resume in real time.

The Workflows runs list in the Vercel dashboard. A run stays Active while it is paused on the signing hook, then flips to Completed once the eSign webhook resumes it.

Opening a completed run shows the whole durable pipeline as a trace. The two Foxit steps run in seconds, the hook span (named by the folderId) accounts for the multi-minute wait while the document sat unsigned, and archiveSigned runs the instant the real folder_executed webhook resumes the workflow.

A completed run trace. generateContract (1.77s) and sendForSignature (1.09s) are the real Foxit calls, the 34624119 span is the hook paused for about three minutes until the document was signed, and archiveSigned (680ms) downloads the executed PDF once the webhook fires.

CRM-Triggered Document Pipeline FAQ

Does the Foxit Document Generation API support formats other than PDF?

Yes. Set outputFormat to "docx" to get a merged Word document back instead of a PDF. That’s useful for contracts that need further edits or approvals before going to eSign.

Can I use the eSign API without DocGen?

Yes. createfolder accepts a PDF from any source, such as a publicly accessible URL, multipart form data, or a base64 string you’ve encoded from an existing file. DocGen and eSign are independent APIs that pair well together because DocGen’s base64 output is exactly what createfolder’s inputType: “base64” mode expects, but neither requires the other.

What happens if a signer doesn’t sign within the expected window?

The folder stays in SHARED or PARTIALLY_SIGNED status indefinitely with no automatic expiry. You’re responsible for detecting stalled folders. In n8n, use a Wait node with a timeout. In Vercel Workflows, use sleep() inside a Promise.race. Both paths let you branch to a follow-up action rather than letting the workflow hang.

How do I handle multiple signers who must sign in order?

Add multiple objects to the parties array with sequential sequence values (1, 2, 3…). The eSign API dispatches to party 2 only after party 1 has signed. Make sure each Text Tag in your template references the correct party number (${signfield:2:y} for party 2’s signature field) and that parties includes a matching entry for every number you use.

How do I keep my eSign Bearer token fresh?

The token response includes expires_in in seconds. Cache the token with a timestamp, check before each call whether you’re within a safe margin of expiry (60 seconds is reasonable), and re-fetch from POST /api/oauth2/access_token when needed. Fetching a new token on every API call adds unnecessary latency and wastes credits.

Can this pipeline handle multiple documents in a single eSign envelope?

Yes. base64FileString is an array. Pass multiple base64-encoded PDFs alongside their corresponding fileNames, and all documents will be included in the same folder for the signer to complete in one session.

What is a CRM-triggered document pipeline and why does it matter?

A CRM-triggered document pipeline is an automated workflow that listens for a CRM event, such as a deal moving to “closed won” in HubSpot, and automatically generates, sends for signature, and archives a contract without human intervention. It matters because manual document handling after a deal closes introduces delays, missed steps, and no audit trail when something fails silently mid-process.

Test End-to-End and Harden for Production

Prove the pipeline by firing a sample deal at the n8n Webhook Test URL with the cURL command from Step 2. Confirm the Document Generation call returns a base64 PDF, the eSign folder is created with a folder.folderId, and the signing email reaches your test address. Running the middle by hand first means you catch a bad credential or a tag mismatch before any nodes downstream depend on it.

Harden the credentials next. Store client_id, client_secret, and the eSign keys as n8n credentials or Vercel environment variables, never as plaintext in node config, and add an n8n error workflow that alerts on any 4xx or 5xx from either Foxit API. Distinguish a 4xx (fix the payload) from a 5xx (retry with backoff).

Finally, size for credits. Each Document Generation call and each eSign send consumes credits, so read the Foxit API credits reference before going to production. The free Developer plan covers 500 credits per year, which is plenty to build and validate the whole pipeline.

Create a free Foxit developer account with no credit card required, grab your Client ID and Secret from the APIs Dashboard, and run your first Document Generation call against the live endpoint before wiring it into a workflow. Create your free account to get started.

Build a CRM-to-eSign Document Pipeline in n8n Using Foxit’s REST APIs

This tutorial shows how to wire the Foxit API n8n integration into a single automated chain. You’ll learn how to generate a PDF, send it for signature, and archive the signed copy without anyone touching a file.

A deal moves to closed-won in the CRM, and then a person takes over. Someone exports the deal fields, pastes them into a contract template, saves a PDF, uploads it to a signing tool, types in the counterparty’s email, and hits send. Days later they check whether it was signed, download the executed copy, and drop it into a shared drive so finance can find it. Every one of those steps is a place where data gets retyped, a wrong template gets attached, or a signature request stalls because nobody was watching.

The failure is structural, not human. The deal data lives in the CRM, the contract template lives in a content folder, the signature lives in a separate vendor, and the archive lives somewhere else again. Nothing connects them, so a person becomes the integration layer.

The target state removes that person from the loop. A CRM event fires, an automation runs a short chain of API calls, and a signed PDF lands in storage with no manual touch. This tutorial builds exactly that using n8n, a source-available workflow tool, as the orchestrator. You will build it step by step, and you do not need to be an n8n expert to follow along. The chain is a CRM webhook, then document generation, then send-for-signature, then an archive step, wired together with n8n’s HTTP Request node.

A Continuous Chain of REST Calls

The pipeline has three stages, and each is a REST call the previous stage feeds directly.

Generate. A CRM webhook delivers deal data into n8n. The workflow merges that data into a Word template and renders a PDF through the Foxit Document Generation API, a cloud REST endpoint with no SDK to install.
Sign. The rendered PDF goes straight to the Foxit eSign API, which creates a signing folder, routes it to the parties, and manages the signature lifecycle.
Archive. When signing completes, the workflow downloads the executed PDF and writes it to storage, then updates the CRM record.

The data handoff between stages is what makes the chain clean. Document Generation returns the finished PDF as a base64 string in its JSON response, and that same base64 string is exactly what the eSign folder-create call accepts as its file payload. No temporary files, no disk writes, and no format juggling between the two calls. The eSign completion event then carries the folder reference the archive stage uses to pull the signed document.

One detail belongs up front, since it shapes every node. The two APIs live on two different hosts. Document Generation runs on https://na1.fusion.foxit.com, and eSign runs on https://na1.foxitesign.foxit.com. They also authenticate differently, which the next section covers. There is no dedicated Foxit node in n8n and none is needed, because both are well-formed REST endpoints that the HTTP Request node handles with custom headers and JSON bodies.

Run n8n Locally and Get Foxit Credentials

The whole tutorial runs on free, self-hosted infrastructure. There is no n8n Cloud plan to sign up for and no paid Foxit tier involved. You run n8n yourself in a container, and the only account you create is Foxit’s free Developer plan.

Install Docker

You need Docker to run n8n. On macOS or Windows, install Docker Desktop; on Linux, install Docker Engine. Both are covered on the Get Docker page. After installing, confirm it works by running docker --version in a terminal.

Start n8n and create your local account

Run the two commands below, taken from n8n’s Docker docs:

docker volume create n8n_data
docker run -it --rm --name n8n -p 5678:5678 \
  -v n8n_data:/home/node/.n8n \
  docker.n8n.io/n8nio/n8n

The n8n_data volume persists your workflows and credentials across restarts, since n8n stores them in a local SQLite database by default. The -p 5678:5678 flag maps the editor to a local port. Now do these steps in order:

Open http://localhost:5678 in your browser.
On first launch, n8n asks you to create an owner account. This is a local account for your own instance, not an n8n Cloud login, so use any email and password you like.
You land on an empty workflow canvas. This is where you will build the pipeline.

Swap -it --rm for -d in the run command when you later want n8n running in the background.

Get your Foxit credentials

Register a Foxit account at account.foxit.com/site/sign-up, verify your email, and activate the free Developer plan. From the APIs Dashboard, copy your Document Generation Client ID and Client Secret. The eSign API is provisioned separately, so once eSign is active on your account, retrieve its Client ID and Client Secret as a distinct pair. You now have two credential sets, and they are not interchangeable.

They differ because the two APIs authenticate differently, and this is the single thing that trips up most first builds. Document Generation takes the credentials as two request headers, lowercase client_id and client_secret, on every call. eSign instead runs an OAuth2 exchange first, trading its credentials for a short-lived bearer token that you then send as an Authorization: Bearer <token> header.

Store the DocGen credentials once, reuse them everywhere

Rather than pasting your Client ID and Secret into every node, store them once in n8n’s credential store. Because Foxit needs two custom headers, use the Custom Auth credential type (the same type Foxit’s own published n8n template uses). In n8n, go to Credentials, click Create credential, search for Custom Auth, click Continue, and paste this JSON:

{
  "headers": {
    "client_id": "YOUR_FOXIT_CLIENT_ID",
    "client_secret": "YOUR_FOXIT_CLIENT_SECRET"
  }
}

The Custom Auth credential holds both Foxit headers in one place. Any HTTP Request node can attach it, so your Client ID and Secret never appear in a node field or an exported workflow.

In this credential, the headers object lists the two headers Foxit expects, with your real Client ID and Secret as the values. Save it, and every Document Generation call in this tutorial can attach it instead of carrying the raw keys.

Import the Finished Workflow (Optional Shortcut)

If you would rather see the whole pipeline first and study it, import the finished version and then follow the step-by-step build below to understand each node. On any workflow canvas, open the ⋯ (Actions) menu in the top right and choose Import from URL….

The Actions menu on the workflow canvas. “Import from URL…” pulls a workflow straight from a link, so there is nothing to download.

Paste the raw URL of the ready-made pipeline JSON and click Import:

https://github.com/lucienchemaly/foxit-demo-templates/raw/main/n8n/foxit-crm-to-esign-pipeline.json

The Import from URL dialog. n8n fetches the JSON and renders the full node graph on the canvas, ready for you to attach your own credentials.

The imported graph arrives with placeholder credentials, so you still create the Custom Auth credential above and select it on the two Foxit nodes. Whether you import or build from scratch, the sections below explain exactly what each node does.

Step 1: Trigger the Workflow and Generate the PDF

Add the trigger and fire it with a test request

Start the workflow with a Webhook node, which is how a CRM will eventually call your pipeline when a deal closes. Click the + on the canvas, search for Webhook, and add it. Set HTTP Method to POST and Path to crm-deal-closed. n8n gives every Webhook node two addresses, a Test URL for building and a Production URL for live traffic.

The Webhook node’s Test URL and “Listen for test event” button. Clicking Listen puts the node in a one-shot capture mode so you can send it a sample request while building.

Because you are working locally and do not have a real CRM pointed at your laptop yet, fire the webhook yourself. Click Listen for test event, copy the Test URL, and send it a sample deal payload with cURL:

curl -X POST "http://localhost:5678/webhook-test/crm-deal-closed" \
  -H "Content-Type: application/json" \
  -d '{
    "company_name": "Acme Robotics",
    "deal_id": "INV-2026-0042",
    "amount": "1875.50"
  }'

In this request, you POST a small JSON object that mimics what a CRM would send when a deal closes. The Webhook node captures it, and those three fields (company_name, deal_id, amount) become available to every downstream node as {{ $json.body.company_name }} and so on. When you later move to production, switch to the node’s Production URL and register it in your CRM’s webhook settings. To expose your local machine to the internet for that, run a tunnel such as ngrok (ngrok http 5678) and register the tunnel address.

Prepare the Word template

The template is an ordinary Word document with Foxit DocGen merge tags where the deal data should land. A tag is a field name in double braces, and you can add Word-style format switches for dates and currency. Download the ready-to-use sample so you do not have to author one, invoice_simple.docx. It carries {{ companyName }}, {{ invoiceNumber }}, {{ invoiceDate \@ MM/dd/yyyy }}, and {{ totalDue \# "$#,##0.00" }}. For repeating rows such as line items, DocGen supports a loop with {{TableStart:lineItems}} and {{TableEnd:lineItems}} markers placed in the same table row, shown in the companion invoice_table.docx. If you want to confirm a template’s tags before wiring it in, POST it once to https://na1.fusion.foxit.com/document-generation/api/AnalyzeDocumentBase64, which returns the full list of tags it detected. The Foxit DocGen quickstart walks through the request shape in more detail.

Add and configure the Generate PDF node

Click + to add an HTTP Request node after the Webhook, and configure it field by field.

Method : set to POST.
URL : https://na1.fusion.foxit.com/document-generation/api/GenerateDocumentBase64
Authentication : choose Generic Credential Type, then Custom Auth, and select the credential you created earlier.
Send Body : turn this on, set the body type to JSON, and paste the payload below.

The HTTP Request node config panel. Every Foxit call in this tutorial is built here by setting the method and URL, attaching the credential, and toggling Send Body on for the JSON payload.

{
  "base64FileString": "<base64-encoded invoice_simple.docx>",
  "documentValues": {
    "companyName": "{{ $json.body.company_name }}",
    "invoiceNumber": "{{ $json.body.deal_id }}",
    "invoiceDate": "2026-07-01",
    "totalDue": "{{ $json.body.amount }}"
  },
  "outputFormat": "pdf"
}

In this body, base64FileString is the Word template encoded as base64, documentValues is a flat object whose keys match the template tags exactly and whose values are pulled from the webhook payload using n8n expressions, and outputFormat is the lowercase string "pdf". The keys in documentValues must match the tag names in the template character for character, since a mismatch renders that field empty rather than raising an error. To turn the template file into the base64 string, fetch it with an HTTP Request node set to return the file, then convert it in a Code node with items[0].binary.data.data, or paste a pre-encoded string while you are testing.

One limit is worth planning for. Document Generation rejects a .docx payload larger than 4 MB measured after base64 encoding, which is roughly a 3 MB raw file, and the rejection comes back as an HTTP 500 rather than a friendly validation message. If your template is heavy, compress its images through Word’s Picture Format pane, drop embedded fonts and OLE objects, and split an oversized template into parts you merge later.

The endpoint is synchronous, so there is no polling. The response is a JSON object with message, fileExtension, and base64FileString, where base64FileString holds the rendered PDF as base64. That value flows straight into Step 2.

Step 2: Exchange an eSign Token and Send for Signature

Get a bearer token

The eSign leg starts by turning your eSign credentials into a bearer token. Add another HTTP Request node and configure it:

Method : POST
URL : https://na1.foxitesign.foxit.com/api/oauth2/access_token
Send Body : on, body type Form Urlencoded, with four fields, grant_type set to client_credentials, client_id set to your eSign Client ID, client_secret set to your eSign Client Secret, and scope set to read-write.

The response is JSON with access_token, token_type (the string bearer), expires_in, and instance_url. This is a standard OAuth2 client-credentials grant as defined in RFC 6749. The token is long-lived but not permanent, so in production cache it and refresh when expires_in is close to elapsing rather than minting a new one on every run.

The token node uses a Form URL Encoded body with the four OAuth fields, not JSON. This is the one eSign call that sends the raw credentials rather than a bearer header.

Click Execute step on this node to confirm it works before wiring the rest. A successful run returns the token in the output panel.

A successful token call. The green check and the access_token / token_type values confirm the credentials and endpoint are correct before you build the next node.

Place signature fields with Text Tags

Signature placement is handled inside the document using Foxit eSign Text Tags, which you type into the Word template while authoring it. The syntax is ${fieldtype:party:mandatory}, so ${signfield:1:y} is a required signature for party 1 and ${datefield:2:n} is an optional date for party 2. If a tag needs to contain a space, replace it with an underscore, because a literal space breaks tag recognition. To keep the tags invisible in the finished document, set their text color to match the page background. On upload you set processTextTags: true, and Foxit converts each tag into a real signing field automatically, which removes any manual drag-and-drop field placement.

There is a party-mapping rule that fails silently, so check it before every send. Every party number referenced by a Text Tag must have a matching entry in the parties array of the create call. If a tag points at party 2 but your parties array only defines party 1, a sendNow: true create still returns success while quietly dropping party 2’s fields, so nobody is ever asked to sign them. Line up the token party numbers with the parties entries first.

Add the Create Signature Folder node

Add a third HTTP Request node for the send-for-signature call:

Method : POST
URL : https://na1.foxitesign.foxit.com/api/folders/createfolder
Send Headers : on, add one header named Authorization with the value Bearer {{ $json.access_token }}, which references the token from the previous node.
Send Body : on, body type JSON, with the payload below.

{
  "folderName": "Contract - {{ $('CRM Webhook').item.json.body.company_name }}",
  "inputType": "base64",
  "base64FileString": ["{{ $('Generate PDF').item.json.base64FileString }}"],
  "fileNames": ["contract.pdf"],
  "processTextTags": true,
  "sendNow": true,
  "parties": [
    {
      "firstName": "Alex",
      "lastName": "Rivera",
      "emailId": "[email protected]",
      "permission": "FILL_FIELDS_AND_SIGN",
      "sequence": 1,
      "workflowSequence": 1
    }
  ]
}

In this call, inputType is set to "base64" and base64FileString is an array holding the PDF that Step 1 produced, which is the direct handoff between the two APIs. The parties array lists each signer with their name, email, and order, processTextTags: true turns the embedded tags into fields, and sendNow: true dispatches the folder for signature in the same request. The response nests the identifier at folder.folderId, which you keep for status tracking and archival. Foxit’s API uses folder terminology throughout rather than envelope. If your process needs a review gate before anything is sent, set sendNow: false to create a draft, then dispatch it later with a POST /api/folders/sendDraftFolder call carrying the returned folderId.

The create-folder node. The Authorization header value Bearer {{ $json.access_token }} pulls the token straight from the previous node, and the input panel on the left shows that token flowing in.

The finished chain in the local n8n editor. Each stage is a plain HTTP Request node, and the base64 PDF from the generation node flows directly into the eSign create-folder node.

Once the folder is sent, the signer receives the document with the Text Tags already converted into interactive fields routed to them.

What the recipient sees after dispatch. This is the visible proof that processTextTags placed the fields correctly and routed them to the right party.

Step 3: Capture Signing Status and Archive the Document

With the folder sent, the workflow needs to know when it is signed so it can archive the result. The folder moves through a defined lifecycle, DRAFT, then SHARED, then PARTIALLY SIGNED, then COMPLETED, then EXECUTED, where the digital signature is applied to the PDF a few seconds after COMPLETED. Archive on the COMPLETED or EXECUTED event so you capture the finalized, digitally signed file.

Foxit eSign can push a webhook when the folder completes, configured in the eSign portal’s owner-only API and Webhooks settings, and you would receive it with a second n8n Webhook node. For a first local build, the simpler path is to poll. Add a Schedule Trigger node paired with an HTTP Request to https://na1.foxitesign.foxit.com/api/folders/viewActivityHistory?folderId={id}, which reads the folder’s audit trail (Created, Invitation Sent, Opened, Viewed, Signed, Folder Executed). This endpoint is GET-only and returns data only once the folder has been shared or sent, so it will not respond for a draft. Gate the next step with an IF node that checks whether the status has reached COMPLETED.

On completion, download the signed PDF through the eSign API and route the binary to a storage node, whether that is Google Drive, an S3 bucket, or an internal file-system node, then fire any downstream updates such as a Slack message or a CRM field write. Because not every send completes, add an error branch as well. If a party declines or the folder expires, route to a separate path that updates the CRM record to reflect the outcome and alerts the deal owner, so a human steps in only on the exceptions.

Common Mistakes and Troubleshooting

A few pitfalls account for most failed first runs.

Wrong host. Document Generation is on na1.fusion.foxit.com; eSign is on na1.foxitesign.foxit.com. Sending a DocGen body to the eSign host (or the reverse) returns an auth or not-found error.
Credential not attached. If a Foxit call comes back 401, the most common cause is an HTTP Request node with Authentication left on None. Attach the Custom Auth credential (DocGen) or add the Authorization: Bearer header (eSign).
Token expired or missing. The eSign bearer token is not permanent. If createfolder returns 401 after the pipeline has been idle, re-run the token node so a fresh access_token flows into the header.
Tag names do not match. A documentValues key that does not exactly match a {{ }} tag renders that field blank with no error. Cross-check the names, or run AnalyzeDocumentBase64 to list the real tags.
Base64 payload too big. An HTTP 500 with a “cannot be larger than 4 MB” body means the encoded .docx exceeded the cap. Slim the template per Step 1.
Party numbers do not line up. A Text Tag pointing at a party not present in the parties array is silently dropped, so that signer is never asked to sign. Match token party numbers to parties entries.

Foxit API n8n FAQ

Do I need a paid plan to test this pipeline?

The free Foxit Developer plan gives you 500 credits per year with instant activation and no credit card required. n8n runs as the source-available Community Edition in Docker with no license key. Both are fully functional for building and testing the complete pipeline described here.

Are the Document Generation and eSign credentials the same?

No. Each API uses its own Client ID and Secret. You will store two separate credential sets in n8n, one for the Document Generation header-based auth and one for the eSign OAuth2 token exchange. They come from separate sections of the Foxit APIs Dashboard.

What if my CRM does not support outbound webhooks?

Use an n8n Schedule node as your trigger. Add an HTTP Request node after it that polls your CRM’s REST API for deals matching your target stage criteria. HubSpot’s Deal Search API and Salesforce’s SOQL query endpoint both support this pattern. The rest of the workflow runs identically from that point forward.

Can I place signature fields without editing the Word template?

Yes. If you prefer not to embed Text Tags in the DOCX, omit processTextTags: true from your createfolder call and place fields manually using the Foxit eSign web editor after the document is uploaded. The manual approach works fine for low-volume workflows but does not scale as cleanly as tag-based automation when the template changes frequently.

What is the lifecycle of a signing folder in Foxit eSign?

A folder moves through five states in order:

DRAFT : created but not sent
SHARED : sent to all parties
PARTIALLY SIGNED : at least one party has signed
COMPLETED : all parties have signed
EXECUTED : the digital signature stamp is applied

Your n8n archival step should trigger on COMPLETED or EXECUTED. If you archive on COMPLETED and need the final stamp, wait for the EXECUTED event instead.

How should I handle token expiry in the eSign OAuth2 flow?

The expires_in field in the token response tells you how long the bearer token is valid. For high-frequency workflows, add a Code node before the createfolder call that checks whether the stored token is still valid and re-requests it if not. You can also request a fresh token at the start of each pipeline execution. The client-credentials grant is stateless, so there is no session overhead to worry about.

How do I debug a merged PDF that returns with blank fields?

Run your template through the Analyze endpoint at POST https://na1.fusion.foxit.com/document-generation/api/AnalyzeDocumentBase64 before executing the full pipeline. It returns every tag the API detects, making it straightforward to catch case mismatches or typos. The merge API performs a case-sensitive lookup, so a template field named {{First_Name}} will not match a JSON key of first_name.

What to Build Next

The fastest way to prove the pipeline is to run the middle of it by hand first. Spin up the local n8n container, activate the free Foxit Developer plan, pull your Client ID and Secret from the APIs Dashboard, and fire the Document Generation POST against invoice_simple.docx from a REST client like Postman or cURL. Once that returns a base64 PDF, you know the hardest call works before any nodes are wired.

From there, two durable extensions are worth building. Save your signing setup as a reusable eSign template with POST /api/templates/createtemplate so future sends skip the field setup, and version the n8n workflow itself by exporting its JSON, so the whole chain can be redeployed or shared across the team.

Building Agentic Document Workflows: How LLM Agents Use PDF APIs to Convert, Extract, and Sign at Scale

This guide walks through building agentic document workflows by exposing Foxit’s PDF and eSign APIs as callable MCP tools, so any compatible agent host can run the full document lifecycle in one automated pipeline.

Agentic document workflows go beyond retrieval, since they convert, transform, merge, and sign documents without human intervention. This guide shows how to expose Foxit’s production PDF API as callable MCP tools so any LLM agent can execute the full document lifecycle (OCR, extraction, generation, and legally binding signatures) in a single automated pipeline.

Most LLM-powered applications have solved the retrieval problem. The harder part of agentic document workflows is action, the moment your agent needs to convert a scanned invoice to searchable text, merge a dozen contract pages into a package, and route it for a legally binding signature without a human in the loop.

RAG gets text into a context window, which is useful for reading. Once you need to produce, transform, or sign a document, you’ve moved into document operations territory. A plain text API won’t close that delta, and bolting together a dozen bespoke REST wrappers every time you need a new pipeline quickly becomes the bottleneck.

The Model Context Protocol (MCP) gives agents a standard way to discover and call tools. Document workflows have been missing a tool surface that exposes real PDF operations as callable MCP tools, backed by a production-ready API. This guide walks through exactly how to build that.

What You Need Before You Start

Five prerequisites are required to follow this guide. You need a Foxit developer account, the open-source MCP server, an MCP-compatible host, three environment variables, and a Python workspace for the signing example.

A Foxit developer account. Sign up at account.foxit.com/site/sign-up (no credit card required for the free Developer plan). The Foxit Developer Portal issues your Client ID and Client Secret, gives you access to the API Playground, and tracks usage in real time.

The open-source MCP server. Clone github.com/foxitsoftware/foxit-pdf-api-mcp-server. The repo ships two active implementations, a Python build (using FastMCP, Python 3.11+, and the uv package manager) and a TypeScript build (Node.js 18+, pnpm). The original stdio-python variant is deprecated, so use the current Python or TypeScript implementation.

An MCP-compatible host. You need somewhere to run the agent. Claude Desktop, Cursor, or VS Code with GitHub Copilot all work, and any MCP-compliant custom agent framework will also connect to the server.

A Python workspace for the signing example. The eSign walkthrough later in this guide runs a short Python script, so you need Python 3.8+ and the requests library. That walkthrough also uses a separate set of eSign credentials, which you set up in its own section rather than here. Scaffold an isolated workspace in one shot:

mkdir agentic-docs && cd agentic-docs
python3 -m venv .venv && source .venv/bin/activate
pip install requests

Three environment variables. Before launching your MCP host process, export these:

export FOXIT_CLOUD_API_HOST="https://na1.fusion.foxit.com/pdf-services"
export FOXIT_CLOUD_API_CLIENT_ID="your_client_id"
export FOXIT_CLOUD_API_CLIENT_SECRET="your_client_secret"

Never hardcode credentials in config files. The MCP server reads these at startup and uses them to authenticate every request to the PDF Services API.

What “Agentic” Actually Means for Document Workflows

An agentic document workflow executes operations on documents (converting formats, applying OCR, merging pages, routing for signature) rather than simply retrieving text from them. The tool surface required is fundamentally different from a RAG setup.

Retrieval-augmented generation pulls text from a document and injects it into a prompt. An agentic document workflow does something to a document, whether it converts a format, applies OCR to make a scanned image searchable, merges pages from multiple sources, or routes the result for signature.

In a tool-use architecture, the LLM doesn’t call the API directly. It picks the right operation from a catalog of tools based on the task, calls it with structured inputs, processes the result, and decides whether to continue the chain or hand off to the next step. If you’ve worked with web-search or code-execution tools in LangChain or AutoGen, the pattern is identical. The model reasons about which tool to invoke, not about how the underlying HTTP request works.

A REST API is an HTTP surface. An MCP tool is a named, typed function with an input schema, an output contract, and a description the model uses to decide when and whether to call it. MCP standardizes that interface so any compliant host can discover the full tool catalog, call individual operations, and chain results without custom adapter code.

A well-designed MCP server eliminates the bespoke integration layer. Without one, every document-heavy agent pipeline requires someone to write and maintain that plumbing from scratch.

Architecture Overview: Two Modes for Agent-Driven PDF Processing

The Foxit PDF API MCP Server wraps Foxit’s cloud PDF Services API as 30+ callable MCP tools, covering every stage of a document lifecycle. Foxit PDF Editor is the first PDF editor in the industry to act as an MCP Host, connecting outward to external MCP Servers and acting on open documents.

Those two facts define two distinct architectural modes.

Mode 1: Programmatic pipeline. Your MCP host (Claude Desktop, Cursor, VS Code with GitHub Copilot, or a custom agent) registers the Foxit PDF API MCP Server. The agent calls PDF tools directly, the server translates those calls into Foxit PDF Services REST requests, and structured results return to the agent. The agent never writes REST plumbing. This is the right model for automated pipelines running without a human in the loop.

Mode 2: In-app orchestration. Foxit PDF Editor acts as the MCP Host. Its embedded AI Assistant connects to external MCP Servers (Jira, Salesforce, Gmail, Notion, GitHub, Google Workspace) and acts on the open document. You could extract fields from a contract PDF and open a Jira ticket without leaving the editor. This is the right model when a knowledge worker needs AI assistance during document review.

Mode 1 is what the rest of this guide builds. Its data flow runs like this:

The agent calls tools, the MCP server handles the REST layer against PDF Services, and a prepared document hands off to eSign at the end of the chain.

One detail to understand before you build is that each successful Foxit PDF Services API call consumes one credit from your plan. Failed requests (4xx or 5xx) do not consume credits. The Developer Dashboard shows real-time usage, so you can see exactly what a pipeline costs per document before scaling it up.

Setting Up the Foxit MCP Server

The server exposes tools across six categories (document lifecycle, creation, conversion, manipulation, security, and forms) plus OCR and document compare.

The full tool catalog breaks down as follows:

Document lifecycle : upload, download, delete
Creation : Word, Excel, PowerPoint, HTML, URL, plain text, and image to PDF
Conversion : PDF to Word, Excel, PowerPoint, HTML, plain text, and image
Manipulation : merge, split, extract pages, compress, flatten, linearize, watermark, and page operations
Security : add and remove passwords, set permissions
Forms : export and import form data as JSON

OCR and document compare are also in the catalog. Signing lives in the eSign API covered in Section 6.

Mode 1: Programmatic Pipeline Setup

Clone the repo and pick your implementation. For the Python version with VS Code and GitHub Copilot, create or update your .vscode/mcp.json with the following:

{
  "servers": {
    "foxit-pdf": {
      "command": "uv",
      "args": [
        "--directory",
        "/absolute/path/to/foxit-pdf-api-mcp-server",
        "run",
        "foxit-pdf-api-mcp-server"
      ],
      "env": {
        "FOXIT_CLOUD_API_HOST": "${env:FOXIT_CLOUD_API_HOST}",
        "FOXIT_CLOUD_API_CLIENT_ID": "${env:FOXIT_CLOUD_API_CLIENT_ID}",
        "FOXIT_CLOUD_API_CLIENT_SECRET": "${env:FOXIT_CLOUD_API_CLIENT_SECRET}"
      }
    }
  }
}

VS Code launches the MCP server as a subprocess through uv, which runs the cloned Python build from its directory. The three ${env:...} references pull credentials from the shell environment instead of hardcoding them in the file, so replace /absolute/path/to/foxit-pdf-api-mcp-server with the path where you cloned the repo and restart VS Code to load the server. Claude Desktop uses the same shape under an mcpServers key and can run the published npm package directly with "command": "npx" and "args": ["-y", "@foxitsoftware/foxit-pdf-api-mcp-server"], so you do not have to clone anything for that host.

Mode 2: In-App Orchestration Setup

Open Foxit PDF Editor, click the AI Assistant tab in the Ribbon, and launch AI Chat to open the right-hand panel. In the bottom left of that panel, click MCP Tools, then click Add MCP Server to configure a new MCP service. Fill in the required fields and save. Once configured, the server appears in the MCP Tools list and its tools activate inside AI Chat.

In both modes, the server reads your Client ID and Client Secret from the environment variables set at startup. No additional gateway configuration is required.

Core Document Operations Agents Can Execute

With the server running, your agent has 30+ callable PDF operations available. Five categories do the heaviest lifting in production pipelines, namely conversion, OCR, structural extraction, merge/split, and document generation via DocGen.

Conversion. An agent receiving an uploaded DOCX triggers the Word-to-PDF creation tool before any downstream step. The output is a standards-compliant PDF that every subsequent operation (OCR, extraction, merge) can work with consistently, eliminating manual conversion and format ambiguity downstream.

OCR. When an agent ingests a scanned or image-only PDF, an OCR call should precede any extraction step. Calling the OCR tool makes the document searchable and text-extractable, which is required for invoice and contract pipelines where key fields sit inside scanned images. The agent calls OCR, waits for the result, and proceeds.

Structural extraction. After OCR, an agent extracts text, tables, and form-field data as structured JSON. Foxit’s structural extraction returns per-page content plus images, giving you a payload that routes cleanly into a BI tool or a second LLM step for analysis or classification. For the full response schema, refer to the Foxit MCP Server developer blog.

Merge and split. An agent assembling a contract package from multiple source documents calls the merge tool with an ordered list of PDFs. An agent pre-processing a large compliance document for parallel LLM analysis calls the split tool to divide it into per-section chunks. Both operations are synchronous and safe to retry on failure.

Document generation via DocGen. For dynamically generated contracts, invoices, or reports, the Foxit Document Generation API accepts a DOCX template with {{dynamic_tags}} and a JSON data payload from a CRM, database, or form response. It returns a finished PDF via POST /document-generation/api/GenerateDocumentBase64. A ready-to-use template lives in the Foxit demos repo if you want to test the call without authoring one. When you upload a DOCX template directly, the 4 MB post-base64 encoding cap applies, so slim templates down by stripping embedded fonts and large images before encoding. The agent supplies the JSON payload at runtime, so a single template can produce thousands of unique documents.

A representative end-to-end pipeline runs like this. An agent ingests a purchase order scan, calls OCR to make it searchable, extracts the structured fields as JSON, merges that data into a contract template via DocGen, and hands the finished PDF off to eSign. Every step is a tool call. The agent reasons about sequencing while the MCP server handles the REST layer.

Agent-Triggered Signing Workflows via the eSign API

Document signing uses a separate REST service, the Foxit eSign API, which has its own credentials and completes the pipeline in three calls. The agent exchanges its credentials for a token, creates a signing folder from the prepared PDF, and dispatches it to the signer.

The eSign API runs on its own host and issues its own Client ID and Client Secret from the eSign portal, separate from the PDF Services credentials the MCP server uses. Export the three eSign variables the script reads before running it:

export FOXIT_ESIGN_BASE_URL="https://na1.foxitesign.foxit.com"
export FOXIT_ESIGN_CLIENT_ID="your_esign_client_id"
export FOXIT_ESIGN_CLIENT_SECRET="your_esign_client_secret"

The folder can only be sent if the signer has a signature field, and the simplest way to place one is with Foxit eSign text tags embedded in the document. Download the ready-to-sign sample, agent_agreement.pdf, into your workspace as agreement.pdf. It already carries the tag that maps a signature field to the first party, so the folder is sendable as is. Then run:

import base64
import os
import requests

BASE_URL = os.environ["FOXIT_ESIGN_BASE_URL"]      # https://na1.foxitesign.foxit.com
CLIENT_ID = os.environ["FOXIT_ESIGN_CLIENT_ID"]
CLIENT_SECRET = os.environ["FOXIT_ESIGN_CLIENT_SECRET"]


def get_access_token():
    resp = requests.post(
        f"{BASE_URL}/api/oauth2/access_token",
        data={
            "client_id": CLIENT_ID,
            "client_secret": CLIENT_SECRET,
            "grant_type": "client_credentials",
            "scope": "read-write",
        },
        timeout=30,
    )
    resp.raise_for_status()
    return resp.json()["access_token"]


def route_for_signature(pdf_path, signer):
    token = get_access_token()
    headers = {"Authorization": f"Bearer {token}", "Content-Type": "application/json"}

    with open(pdf_path, "rb") as fh:
        encoded = base64.b64encode(fh.read()).decode()

    folder = requests.post(
        f"{BASE_URL}/api/folders/createfolder",
        headers=headers,
        json={
            "folderName": "Agent Service Agreement",
            "inputType": "base64",
            "base64FileString": [encoded],
            "fileNames": ["agreement.pdf"],
            "processTextTags": True,
            "sendNow": False,
            "parties": [
                {
                    "permission": "FILL_FIELDS_AND_SIGN",
                    "firstName": signer["first_name"],
                    "lastName": signer["last_name"],
                    "emailId": signer["email"],
                    "sequence": 1,
                }
            ],
        },
        timeout=60,
    )
    folder.raise_for_status()
    folder_id = folder.json()["folder"]["folderId"]

    sent = requests.post(
        f"{BASE_URL}/api/folders/sendDraftFolder",
        headers=headers,
        json={"folderId": folder_id},
        timeout=60,
    )
    sent.raise_for_status()
    return folder_id


if __name__ == "__main__":
    fid = route_for_signature(
        "agreement.pdf",
        {"first_name": "Jordan", "last_name": "Lee", "email": "[email protected]"},
    )
    print(f"Folder {fid} sent for signature")

In this code, you read the eSign credentials from the environment and exchange them for a bearer token at the access_token endpoint, where the request is form-encoded rather than JSON (sending JSON returns a 415). You then base64-encode the local PDF and post it to createfolder with inputType set to base64 so the API reads the base64FileString array, with processTextTags set to True so the document’s text tags become a real signature field, and with sendNow set to False so the folder is created as a draft instead of emailing anyone immediately. The parties array names the signer with FILL_FIELDS_AND_SIGN permission, you read the new id at folder.folderId, and you pass it to sendDraftFolder, which dispatches the draft to the signer. To confirm the result, call GET /api/folders/viewActivityHistory?folderId={id}, which returns the activity log once the folder has been shared (a draft returns logs of a non-shared folder can not be viewed). Foxit uses “folder” throughout the eSign API, never “envelope.”

Compliance is built into the API layer. The Foxit eSign API supports eIDAS, the ESIGN Act, UETA, HIPAA, and GDPR, covering the requirements for agents operating in legal, healthcare, and finance contexts. No separate compliance infrastructure is required.

Production Considerations: Compliance, Cost, and Error Handling

The Foxit PDF Services and eSign APIs are SOC 2 Type II certified, with HIPAA BAA support, GDPR compliance, and CCPA coverage built in. Three additional concerns (credit consumption, idempotency, and async polling) determine whether a pipeline runs reliably at scale.

Credit consumption. The free Developer plan includes 500 credits per year (annual reset, no rollover). The Startup plan is $1,750/year for 3,500 credits. The Business plan is $4,500/year for 150,000 credits. Each successful API call consumes one credit; 4xx and 5xx responses do not. A pipeline processing 50 documents per day burns through those allocations quickly. Monitor real-time usage in the Developer Dashboard before moving to production and size your plan accordingly.

Idempotency. Merge, flatten, and convert calls are safe to retry on failure. Signing-folder creation is not, so gate createfolder behind a state check so the agent doesn’t create duplicate folders and dispatch duplicate signing requests to the same signers.

Async operations. Translation and batch conversion operations are asynchronous, so they return a job ID immediately, and your agent should poll the job status endpoint roughly every three seconds until the status is COMPLETED or FAILED before proceeding to the next step in the chain. Handling these concerns at build time separates a working pipeline from one that generates support tickets.

Common Mistakes

Dropping the /api/ prefix on eSign calls : Every eSign path lives under /api/, as in /api/folders/createfolder. Omitting it returns a 404 against a docs-style path that does not exist.
Sending the token request as JSON : The access_token endpoint is form-encoded. A JSON body returns 415 Unsupported Media Type, so pass the credentials as form data.
Forgetting inputType: base64 : When you send a base64 PDF without it, createfolder rejects the request with fileUrls or base64FileString cannot be empty. URL mode uses fileUrls and fileNames instead.
Sending a signer with no signature field : A FILL_FIELDS_AND_SIGN party needs a field. If the document has no text tag like ${s:1:______} and you skip processTextTags, sendDraftFolder returns Please assign a signature field. Use underscores in the tag placeholder, since an empty placeholder does not create a field.
Expecting a signing tool in the MCP server : The 30+ MCP tools cover PDF operations, not signatures. Signing is the eSign API, a separate service with separate credentials.

Agentic Document Workflows FAQ

What is an agentic document workflow?

An agentic document workflow is an automated pipeline in which an LLM agent executes operations on documents (conversion, OCR, extraction, merging, generation, and signing) without human intervention. Unlike retrieval-augmented generation, which only reads documents, an agentic workflow produces and transforms them using callable tools exposed through a protocol like MCP.

How does the Model Context Protocol (MCP) work with PDF APIs?

MCP defines a standard interface for exposing named, typed functions, called tools, that an LLM agent can discover and invoke. A PDF API MCP server wraps REST endpoints as MCP tools with input schemas and output contracts. The agent selects the right tool based on task context, calls it with structured parameters, and processes the result, without writing any HTTP request logic.

What PDF operations does the Foxit MCP server expose?

The Foxit PDF API MCP Server exposes 30+ tools covering document lifecycle (upload, download, delete), creation (Word, Excel, PowerPoint, HTML, image to PDF), conversion (PDF to multiple formats), manipulation (merge, split, compress, OCR, watermark), security (password management), and forms (JSON import/export).

Does every API call consume a credit even if it fails?

No. Only successful Foxit PDF Services API calls consume credits. Requests that return 4xx or 5xx status codes do not count against your plan. The Developer Dashboard provides real-time usage tracking so you can measure pipeline cost per document before scaling.

How do I trigger document signing from an agent without human intervention?

After preparing a document, your agent calls the Foxit eSign API directly. It authenticates with client_credentials, POSTs to /api/folders/createfolder with the base64 PDF and a parties entry for the signer, then POSTs to /api/folders/sendDraftFolder with the returned folderId. The signing email workflow triggers automatically, and the agent can poll /api/folders/viewActivityHistory for the audit trail.

What compliance standards does the Foxit eSign API meet?

The Foxit eSign API supports eIDAS, the U.S. ESIGN Act, UETA, HIPAA, GDPR, and CCPA. The PDF Services API is SOC 2 Type II certified with HIPAA BAA support. No separate compliance wrappers are required for agents operating in legal, healthcare, or financial contexts.

What is the difference between Mode 1 and Mode 2 in the Foxit MCP architecture?

Mode 1 is a programmatic pipeline where an external LLM agent (Claude Desktop, Cursor, VS Code with GitHub Copilot, or a custom framework) registers the Foxit MCP Server and calls PDF tools automatically. Mode 2 is in-app orchestration where Foxit PDF Editor acts as the MCP Host, connecting to external services like Jira or Salesforce while a knowledge worker reviews the open document.

Why should signing-folder creation be gated behind a state check?

The /api/folders/createfolder endpoint is not idempotent. If an agent retries on failure without a state check, it will create duplicate folders and send duplicate signing requests to the same signers. Merge, flatten, and convert operations are safe to retry; folder creation requires the agent to verify no existing folder was created before calling the endpoint again.

Start Building: Free Developer Access in Minutes

The full pipeline in this guide is available to test today. Activate a free Foxit Developer plan to get your Client ID, Client Secret, access to the API Playground, and 500 credits for real requests. No credit card required.

Clone the open-source MCP server, export the three environment variables, and register the server in Claude Desktop, Cursor, or VS Code with GitHub Copilot. At that point, 30+ PDF tools are callable from your agent with no local SDK to install and no REST plumbing to write.

Once a document is prepared, extend the pipeline into legally binding signatures with the eSign API. The architecture in this guide covers the full document lifecycle from conversion and OCR through extraction, generation, merging, and signing, all in a single agentic document workflow.

Create your free developer account to clone the open-source MCP server and make 30+ PDF tools callable from your agent in minutes, no credit card required.

Create Custom Invoices with Word Templates and Foxit Document Generation

This tutorial shows how to design a Word invoice template with dynamic tokens and use Foxit’s Document Generation API and a short Python script to turn JSON data into polished, ready-to-send PDF invoices.

Manual invoice processing costs between $18 and $26 per invoice, while automated workflows bring that down to $2.50 to $4, according to industry accounts-payable benchmarks. Foxit’s Document Generation API generates well-formatted, dynamic PDF invoices from your existing data, which eliminates manual data entry, formatting errors, and the overhead of per-invoice handling. This tutorial shows you how to build that workflow end to end.

Before You Start

To follow along, grab your free credentials on the developer portal and read the introductory guide to automated document pipelines, which covers the basics of working with the API.

The API works with Microsoft Word templates containing tokens wrapped in double brackets. You pass the template and your data to the API, it replaces those tokens with your data values, and returns a PDF (or Word file, if you prefer).

Prerequisites

This tutorial runs a short Python script, so set up the following before you start:

Python 3.12 or newer. The script uses an f-string syntax introduced in Python 3.12.
pip for installing packages, plus the built-in venv module for an isolated environment.
The requests library for the HTTP call.
A code editor such as VS Code with the Python extension. PyCharm, WebStorm, or Sublime Text work too.
curl if you want to hit the endpoint from the command line first.
A Foxit developer account. Sign up for free to get your Client ID and Client Secret.

Scaffold the workspace in one shot:

mkdir foxit-invoices && cd foxit-invoices
python3 -m venv .venv
source .venv/bin/activate
pip install requests

Then export your credentials and host so the script can read them from the environment:

export CLIENT_ID="your_client_id"
export CLIENT_SECRET="your_client_secret"
export HOST="https://na1.fusion.foxit.com"

Designing Your Invoice Word Template

Template design in Word is your starting point. An invoice typically includes:

The customer receiving the invoice
The invoice number and issue date
The payment due date
A line-item table with product name, quantity, price, and a running total

The Document Generation API places no constraints on template design. Size, alignment, and styling can match your corporate standards, whether that means a simple layout or a polished, branded one. Consider the template below (download link at the end of this article):

The Word template with double-bracket tokens that the Document Generation API replaces at runtime.

Working from the top of the template:

{{ invoiceNum }} is the invoice number for the customer.
{{ today \@ MM/dd/yyyy }} combines a built-in value (today, which represents the current date at API call time) with a date mask that controls the display format. The API docs list all available masks.
{{ accountName }} is a standard token mapped directly from your data.
{{ paymentDueDate \@ MM/dd/yyyy }} demonstrates date masks applied to dates from your own data, not just built-ins.
The line-item table uses one header row and one data row. The dynamic row opens with {{TableStart:lineItems}} (where lineItems is the name of an array in your JSON) and closes with {{TableEnd:lineItems}}. Between those markers sit product, qty, price, totalPrice, and ROW_NUMBER (a built-in that auto-increments from 1). The \# Currency format applied to totalPrice renders it as a formatted currency value.
A final table row uses SUM(ABOVE) with currency formatting to total the column.

Structuring Your Invoice Data as JSON

In a production system, invoice data typically comes from a database or e-commerce API. For this demo, it comes from a JSON file:

[
  {
    "invoiceNum": 100,
    "accountName": "Customer Alpha",
    "accountNumber": 1,
    "paymentDueDate": "August 15, 2025",
    "lineItems": [
      { "product": "Product 1", "qty": 5, "price": 2, "totalPrice": 10 },
      { "product": "Product 5", "qty": 3, "price": 9, "totalPrice": 18 },
      { "product": "Product 4", "qty": 1, "price": 50, "totalPrice": 50 },
      { "product": "Product X", "qty": 2, "price": 15, "totalPrice": 30 }
    ]
  },
  {
    "invoiceNum": 25,
    "accountName": "Customer Beta",
    "accountNumber": 2,
    "paymentDueDate": "August 15, 2025",
    "lineItems": [
      { "product": "Product 2", "qty": 9, "price": 2, "totalPrice": 18 },
      { "product": "Product 4", "qty": 1, "price": 8, "totalPrice": 8 },
      { "product": "Product 3", "qty": 10, "price": 25, "totalPrice": 250 },
      { "product": "Product YY", "qty": 3, "price": 15, "totalPrice": 45 },
      { "product": "Product AA", "qty": 2, "price": 100, "totalPrice": 200 }
    ]
  },
  {
    "invoiceNum": 51,
    "accountName": "Customer Gamma",
    "accountNumber": 3,
    "paymentDueDate": "August 15, 2025",
    "lineItems": [
      { "product": "Product 9", "qty": 1, "price": 2, "totalPrice": 2 },
      { "product": "Product 23", "qty": 30, "price": 9, "totalPrice": 270 },
      { "product": "Product ZZ", "qty": 6, "price": 15, "totalPrice": 90 }
    ]
  }
]

The array holds three invoice objects, each matching the structure of the Word template. The accountNumber field has no matching template token, and that’s intentional. Your data can contain fields the template doesn’t use, and accountNumber is used in the Python script to build unique output filenames.

Calling the Document Generation API with Python

The Generate Document endpoint requires your credentials, a base64-encoded version of the template, and your data. The complete demo runs in just over 50 lines of Python:

import os
import requests
import sys
from time import sleep
import base64
import json
from datetime import datetime

CLIENT_ID = os.environ.get('CLIENT_ID')
CLIENT_SECRET = os.environ.get('CLIENT_SECRET')
HOST = os.environ.get('HOST')

def docGen(doc, data, id, secret):

	headers = {
		"client_id":id,
		"client_secret":secret
	}

	body = {
		"outputFormat":"pdf",
		"documentValues": data,
		"base64FileString":doc
	}

	request = requests.post(f"{HOST}/document-generation/api/GenerateDocumentBase64", json=body, headers=headers)

	return request.json()

with open('invoice.docx', 'rb') as file:
	bd = file.read()
	b64 = base64.b64encode(bd).decode('utf-8')

with open('invoicedata.json', 'r') as file:
	data = json.load(file)

for invoiceData in data:
	result = docGen(b64, invoiceData, CLIENT_ID, CLIENT_SECRET)

	if result["base64FileString"] == None:
		print("Something went wrong.")
		print(result)
		sys.exit()

	b64_bytes = result["base64FileString"].encode('ascii')
	binary_data = base64.b64decode(b64_bytes)

	filename = f"invoice_account_{invoiceData["accountNumber"]}.pdf"

	with open(filename, 'wb') as file:
		file.write(binary_data)
		print(f"Done and stored to {filename}")

After importing modules and loading credentials from environment variables, the docGen function takes the template, data, and credentials, then posts to the API endpoint. The API returns the rendered PDF as a base64 string.

The main loop reads and base64-encodes the template, loads the JSON file, iterates over each invoice object, calls the API, and writes the result to a uniquely named file using accountNumber. You don’t have to write results to disk at all, since the raw binary data can go straight to an email attachment or a document storage system.

Keep one limit in mind, since the GenerateDocumentBase64 endpoint rejects a .docx payload larger than 4 MB after base64 encoding. If your template approaches that ceiling, compress its images through Word’s Picture Format tools, drop embedded fonts and OLE objects, and split oversized templates into smaller ones.

The rendered PDF invoice the script produces, with all tokens replaced by values from the JSON payload.

Generate Invoice PDF API FAQ

What output formats does the Document Generation API support?

The API returns either a PDF or a DOCX file. You specify the format in the outputFormat field of the request body, as shown in the Python example above.

Can I use live data from a CRM or database instead of a JSON file?

Yes. The documentValues parameter accepts any JSON-serializable object, so you can pull data from Salesforce, a SQL database, a REST endpoint, or any other source and pass it directly to the API. The JSON file in this tutorial is a stand-in for whatever data source you use in production.

Do I need special Foxit software to design the Word template?

No. You design templates in standard Microsoft Word. The API reads the token syntax ({{ }}) from any valid .docx file, with no Foxit desktop software or proprietary editor required.

Is the API compliant with data security requirements?

Foxit’s API platform is SOC 2 Type II certified and supports GDPR and HIPAA compliance, which makes it suitable for invoices that include customer personally identifiable information or regulated financial data. See Foxit’s API security and compliance page for the full list of frameworks.

How do I get started without paying upfront?

The free Developer plan gives you instant access. It covers this tutorial and experimentation with your own templates before committing to a paid tier.

Next Steps

Get free credentials and download the template, Python script, and sample output from the GitHub repository to run this demo yourself.

Two natural extensions follow from here. Foxit Connectors provides 40+ pre-built integrations with platforms like Salesforce, SharePoint, and Google Drive, so you can pull invoice data directly from your CRM or ERP rather than a local JSON file. You can also chain document generation with an eSign step, sending the invoice for client acknowledgment immediately after creation, by passing the generated PDF to the Foxit eSign API.

Programmatic PDF Editing with Foxit PDF Services API: Pages, Merges, Splits, and Flattening at Scale

Manually editing PDFs doesn’t scale when you’re processing hundreds of documents a day. This guide uses working Python and cURL examples to walk through the Foxit PDF Editor API’s core operations, covering page manipulation, merging, splitting, and flattening.

If you’re building document workflows at scale, you already know that manual PDF editing doesn’t cut it. Whether you’re generating contracts, processing invoices, or packaging reports, you need an API that handles page manipulation, merging, splitting, and flattening without breaking under load. Foxit PDF Services API gives you exactly that.

This guide covers the operations you’ll use most: adding and removing pages, merging documents, splitting by page range, and flattening annotations and form fields. Code examples are in Python, but the API is REST-based, so the patterns translate to any stack.

What Is the Foxit PDF Services API?

Foxit PDF Services API is a cloud-based REST API for programmatic PDF manipulation. You send documents and parameters; it returns processed PDFs. No local dependencies, no rendering engine to maintain.

The API handles:

Page insertion, deletion, and reordering
Document merging (combining multiple PDFs into one)
Document splitting (breaking one PDF into multiple outputs)
Flattening (converting annotations, form fields, and overlays into static page content)

Authentication uses API keys. Every request requires client_id and client_secret as separate HTTP request headers.

Why Backend PDF Editing Is an Infrastructure Decision

Teams processing hundreds of PDFs a day have an architecture problem, not a tooling problem.

When your CRM spits out contracts, your ERP generates invoices, and your intake forms produce patient records, the question is how you process these at scale without standing up a server farm or babysitting a library version matrix. At 500+ documents per day, manual desktop tooling is off the table. Per-file scripts that depend on a locally installed library become a liability the moment the library version shifts or a new language target appears.

Two architectural approaches dominate this space: SDK-based libraries and cloud REST APIs. SDK libraries require local installation, version pinning, language-specific bindings, and ongoing maintenance every time a dependency shifts. A cloud REST API requires none of that. Any language that can send an HTTP request can call it, with no package to install, no runtime to configure, and no compatibility matrix to manage.

This guide covers four operations in full: page manipulation (move, rotate, delete, add), merging multiple PDFs into one output, splitting a large document by page count, and flattening annotations into permanently static content. All of it runs via REST calls against the Foxit PDF Services API, authenticated with two request headers and structured around a single four-step loop that applies to every endpoint in the suite.

Prerequisites

Get your environment in order before any code runs. Each tool links to its canonical install page.

Python 3.8+
pip
venv for project isolation
requests library
Node.js 18+ and npm
axios for Node examples
cURL CLI
A code editor such as VS Code with the Python extension; alternatives include PyCharm, WebStorm, and Sublime Text
Postman (optional, for API exploration alongside the Foxit API Playground)
A Foxit developer account, available at account.foxit.com/site/sign-up with no credit card required and free credits included

Set up your workspace:

mkdir foxit-pdf-tutorial && cd foxit-pdf-tutorial

python3 -m venv .venv

source .venv/bin/activate

pip install requests

Authentication and the Upload → Task → Poll → Download Loop

Authentication

Foxit PDF Services API authenticates via headers. Every request must include client_id and client_secret as separate HTTP request headers, exactly as named: lowercase, underscored. They’re passed individually, as plain strings. Concatenating them, Base64-encoding them, or prefixing them with Bearer are all auth mistakes that look like they should work and don’t.

The base host for the North America environment is https://na1.fusion.foxit.com. Set it once as an environment variable and reuse it:

export BASE_URL="https://na1.fusion.foxit.com"

export CLIENT_ID="your_client_id"

export CLIENT_SECRET="your_client_secret"

Every cURL request in this guide uses that pattern:

--header "client_id: $CLIENT_ID"

--header "client_secret: $CLIENT_SECRET"

In Python, read credentials from os.environ and never hardcode them:

import os

import time

import requests

  

BASE_URL = os.environ["BASE_URL"]

CLIENT_ID = os.environ["CLIENT_ID"]

CLIENT_SECRET = os.environ["CLIENT_SECRET"]

  

headers = {

"client_id": CLIENT_ID,

"client_secret": CLIENT_SECRET,

}

In Node.js:

const axios = require("axios");

  

const BASE_URL = process.env.BASE_URL;

const headers = {

client_id: process.env.CLIENT_ID,

client_secret: process.env.CLIENT_SECRET,

};

The Four-Step Loop

Every operation in this API follows the same four steps, regardless of endpoint.

POST /pdf-services/api/documents/upload with the file as multipart/form-data. The response returns an upload documentId.
POST to the relevant endpoint (manipulate, combine, split, or flatten) with the upload documentId in the request body. The response is HTTP 202 with a taskId.
GET /pdf-services/api/tasks/{task-id} until the status field reads COMPLETED. The completed task response also carries a resultDocumentId and a progress percentage. Task statuses are always uppercase: PENDING, PROCESSING, COMPLETED, FAILED.
GET /pdf-services/api/documents/{resultDocumentId}/download to retrieve your result. The upload documentId from step one and the resultDocumentId from step three are different identifiers. You download using the resultDocumentId. Swapping these is the most common 4xx error.

Use a-midsummer-nights-dream.pdf to follow along with a known-good file:

curl --location "$BASE_URL/pdf-services/api/documents/upload" \

--header "client_id: $CLIENT_ID" \

--header "client_secret: $CLIENT_SECRET" \

--form 'file=@"a-midsummer-nights-dream.pdf"'

Response:


{

"documentId": "abc123-upload-id"

}

A reusable Python polling function with exponential backoff:


def poll_task(task_id: str) -> str:

url = f"{BASE_URL}/pdf-services/api/tasks/{task_id}"

delay = 2

while True:

response = requests.get(url, headers=headers)

response.raise_for_status()

data = response.json()

status = data["status"]

if status == "COMPLETED":

return data["resultDocumentId"]

elif status == "FAILED":

raise RuntimeError(f"Task {task_id} failed: {data}")

time.sleep(delay)

delay = min(delay * 2, 30)

Branch on "COMPLETED" and "FAILED" in uppercase. Lowercase strings will silently never match.

The async model is what makes this scalable. A 50-page merge or a batch of 200 splits doesn’t block your thread while it runs. You dispatch the operation call, collect the taskId, and poll on a sensible backoff schedule. At 500+ PDFs per day, that non-blocking pattern keeps your worker pool from saturating.

Page Manipulation: Move, Rotate, Delete, and Add Pages

All page operations go through a single endpoint: POST /pdf-services/api/documents/modify/pdf-manipulate.

{

"documentId": "<upload-document-id>",

"password": "optional",

"config": {

"operations": [{ "type": "OPERATION_TYPE" }]

}

}

The config.operations array runs in order. Page indexing is 1-based and adjusts after each step. If you delete page 3 and then reference page 4 in the next operation, that reference points to what was originally page 5 before the delete. Keep that in mind when chaining operations in a single request.

MOVE_PAGES

MOVE_PAGES reorders pages within the document:

{

"type": "MOVE_PAGES",

"pages": [5, 6, 7],

"targetPosition": 1

}

targetPosition is 1-based and must not exceed the document’s total page count.

ROTATE_PAGES

ROTATE_PAGES changes page orientation:

{

"type": "ROTATE_PAGES",

"pages": [1, 2, 3],

"rotation": "ROTATE_CLOCKWISE_90"

}

Valid rotation values are ROTATE_0, ROTATE_CLOCKWISE_90, ROTATE_180, and ROTATE_COUNTERCLOCKWISE_90.

DELETE_PAGES

DELETE_PAGES removes specific pages:


{

"type": "DELETE_PAGES",

"pages": [8, 9]

}

ADD_PAGES

ADD_PAGES appends blank pages to the end of the document:


{

"type": "ADD_PAGES",

"pageCount": 2

}

ADD_PAGES has no insert-at-position parameter; blank pages always go to the end. There’s also no REPLACE_PAGES operation in the current API. Page replacement requires a DELETE_PAGES call on the target pages followed by a separate merge step to bring in the replacement content.

A document intake pipeline for scanned medical records often receives pages in landscape orientation when the archive standard is portrait. The Python call below normalizes pages 1 through 3 of the uploaded file:

def rotate_pages(document_id: str) -> str:

url = f"{BASE_URL}/pdf-services/api/documents/modify/pdf-manipulate"

payload = {

"documentId": document_id,

"config": {

"operations": [

{

"type": "ROTATE_PAGES",

"pages": [1, 2, 3],

"rotation": "ROTATE_CLOCKWISE_90"

}

]

}

}

response = requests.post(url, json=payload, headers=headers)

response.raise_for_status()

return response.json()["taskId"]

A legal document workflow that assembles exhibits and needs to move pages 5, 6, and 7 to the front before archiving uses this request body:


{

"documentId": "<upload-document-id>",

"config": {

"operations": [

{

"type": "MOVE_PAGES",

"pages": [5, 6, 7],

"targetPosition": 1

}

]

}

}

All four operation types return HTTP 202 with a taskId. Pass that ID to poll_task, wait for COMPLETED, then download the resultDocumentId.

Merging and Splitting PDFs

Merging Multiple PDFs with pdf-combine

The merge endpoint is POST /pdf-services/api/documents/enhance/pdf-combine.

The request body takes a required documentInfos array. Each entry is a source document object:


{

"documentInfos": [

{ "documentId": "<doc-id-1>" },

{ "documentId": "<doc-id-2>" },

{ "documentId": "<doc-id-3>" }

],

"config": {

"addBookmark": true,

"continueMergeOnError": false,

"retainPageNumbers": false

}

}

The config object supports three keys:

addBookmark generates one bookmark per source file in the merged output, useful when the reader needs to navigate by source.
retainPageNumbers preserves original page-number labels from each source.
continueMergeOnError is the one that matters most in production. Set it to false for any job where a single bad source must fail the entire batch. Set it to true only for best-effort pipelines where partial output is acceptable. Always set it explicitly rather than relying on defaults.

The following code assembles a monthly client report from three sources. Download input.pdf, second.pdf, and input_for_compare.pdf to run this end-to-end:


def upload_file(path: str) -> str:

url = f"{BASE_URL}/pdf-services/api/documents/upload"

with open(path, "rb") as f:

response = requests.post(url, headers=headers, files={"file": f})

response.raise_for_status()

return response.json()["documentId"]

  

def merge_pdfs(document_ids: list) -> str:

url = f"{BASE_URL}/pdf-services/api/documents/enhance/pdf-combine"

payload = {

"documentInfos": [{"documentId": doc_id} for doc_id in document_ids],

"config": {

"addBookmark": True,

"continueMergeOnError": False,

"retainPageNumbers": False

}

}

response = requests.post(url, json=payload, headers=headers)

response.raise_for_status()

return response.json()["taskId"]

  

# Upload all three source files, collect their documentIds

doc_ids = [

upload_file("input.pdf"),

upload_file("second.pdf"),

upload_file("input_for_compare.pdf")

]

  

# Merge and download

merge_task_id = merge_pdfs(doc_ids) # POST combine → taskId

merge_result_id = poll_task(merge_task_id) # poll → resultDocumentId

Once poll_task returns a resultDocumentId, pass it to your download function.

Splitting a PDF by Page Count with pdf-split

The split endpoint is POST /pdf-services/api/documents/modify/pdf-split. The pdf- prefix is required and matches the naming convention used by pdf-combine, pdf-manipulate, and pdf-flatten.

The request body is minimal:


{

"documentId": "<upload-document-id>",

"pageCount": 10

}

pageCount specifies how many pages go into each output file. The last file gets whatever pages remain. The current API exposes only this page-count split mode. File-size-based and bookmark-based splitting are not in the published reference.

curl --location "$BASE_URL/pdf-services/api/documents/modify/pdf-split" \

--header "client_id: $CLIENT_ID" \

--header "client_secret: $CLIENT_SECRET" \

--header 'Content-Type: application/json' \

--data '{

"documentId": "<upload-document-id>",

"pageCount": 10

}'

The response returns a taskId. When polling reaches COMPLETED, the result contains multiple output files, one per split chunk.

Flattening Annotations: Making PDF Changes Permanent

Flattening merges annotations, form fields, and layers into the page content itself. The output is a single static PDF where no markup can be toggled, filled, or removed. This is a one-way transformation with no undo.

The endpoint is POST /pdf-services/api/documents/modify/pdf-flatten.

The request body is intentionally minimal:


{

"documentId": "<upload-document-id>"

}

No flags for selective annotation or form-field handling are exposed in the current API reference. The operation flattens both annotations and form fields together in a single pass.

When to Flatten a PDF

Flattening is required in three situations:

Archiving a signed form. Without flattening, a technically capable recipient can still manipulate form fields in most PDF viewers, even after signature. Flattening removes that possibility entirely.
Print production. Annotation layers render differently across print drivers and produce visible artifacts in the final output. Flattening eliminates the variable.
Compliance workflows under HIPAA or legal hold. Documents at rest must be immutable. A live form field fails that requirement.

curl --location "$BASE_URL/pdf-services/api/documents/modify/pdf-flatten" \

--header "client_id: $CLIENT_ID" \

--header "client_secret: $CLIENT_SECRET" \

--header 'Content-Type: application/json' \

--data '{ "documentId": "<upload-document-id>" }'

Flattening does not encrypt the document or apply password protection. If your workflow requires both, chain a pdf-protect call after flattening using POST /pdf-services/api/documents/security/pdf-protect, passing the resultDocumentId from the completed flatten task as the documentId input for the protect call and the password under config.userPassword. The result of one operation becomes the input of the next.


{

"documentId": "<flatten-result-document-id>",

"config": {

"userPassword": "<password>"

}

}

In this body, you point documentId at the flatten task’s resultDocumentId and set the open password under config.userPassword. The password lives inside the config object, not at the top level. A top-level password key is accepted by the request but the task then fails with a parameter error, so nest it under config.

Building a Multi-Step PDF Editing Pipeline for High Volume

Chaining Operations with resultDocumentId

Every completed task returns a resultDocumentId. That ID becomes the documentId for the next operation. The full chain: upload, then operation A, then poll until A reaches COMPLETED, then operation B using A’s resultDocumentId, then poll until B reaches COMPLETED, then download B’s resultDocumentId.

A complete flatten-then-protect pipeline, with inline comments showing which ID type is active at each step:


import os

import time

import requests

  

BASE_URL = os.environ["BASE_URL"]

CLIENT_ID = os.environ["CLIENT_ID"]

CLIENT_SECRET = os.environ["CLIENT_SECRET"]

  

headers = {

"client_id": CLIENT_ID,

"client_secret": CLIENT_SECRET,

}

  

def upload_file(path: str) -> str:

url = f"{BASE_URL}/pdf-services/api/documents/upload"

with open(path, "rb") as f:

response = requests.post(url, headers=headers, files={"file": f})

response.raise_for_status()

return response.json()["documentId"]

  

def poll_task(task_id: str) -> str:

url = f"{BASE_URL}/pdf-services/api/tasks/{task_id}"

delay = 2

while True:

response = requests.get(url, headers=headers)

response.raise_for_status()

data = response.json()

status = data["status"]

if status == "COMPLETED":

return data["resultDocumentId"]

elif status == "FAILED":

raise RuntimeError(f"Task failed: {data}")

time.sleep(delay)

delay = min(delay * 2, 30)

  

def flatten(document_id: str) -> str:

url = f"{BASE_URL}/pdf-services/api/documents/modify/pdf-flatten"

response = requests.post(url, json={"documentId": document_id}, headers=headers)

response.raise_for_status()

return response.json()["taskId"]

  

def protect(document_id: str, password: str) -> str:

url = f"{BASE_URL}/pdf-services/api/documents/security/pdf-protect"

payload = {"documentId": document_id, "config": {"userPassword": password}}

response = requests.post(url, json=payload, headers=headers)

response.raise_for_status()

return response.json()["taskId"]

  

def download(document_id: str, output_path: str):

url = f"{BASE_URL}/pdf-services/api/documents/{document_id}/download"

response = requests.get(url, headers=headers)

response.raise_for_status()

with open(output_path, "wb") as f:

f.write(response.content)

  

# Pipeline: upload → flatten → protect → download

upload_doc_id = upload_file("signed-form.pdf") # documentId

flatten_task_id = flatten(upload_doc_id) # taskId

flatten_result_id = poll_task(flatten_task_id) # resultDocumentId

protect_task_id = protect(flatten_result_id, os.environ["PDF_PASSWORD"]) # taskId

protect_result_id = poll_task(protect_task_id) # resultDocumentId

download(protect_result_id, "final-protected.pdf")

Three distinct IDs flow through this pipeline: the upload documentId, the taskId returned by each operation call, and the resultDocumentId returned by each completed task. Confusing any two of these produces a 4xx.

Batch Polling for High-Volume Jobs

For a single document, sequential polling works fine. For a batch of thousands, polling each task one at a time becomes the bottleneck. The pattern that scales is to dispatch first, then consolidate.

Upload all source files in parallel and collect their documentIds. Dispatch all operation calls in parallel and collect their taskIds. Then run a single consolidated polling loop that iterates over all taskIds, checks each status, and branches on COMPLETED or FAILED per task. Your thread never blocks waiting for one document while others are already done, and it processes results as they arrive.

The multi.py sample in the foxitsoftware/developerapidemos repository demonstrates this exact dispatch-then-consolidate shape, including the resultDocumentId handoff across operations.

Common Mistakes and Troubleshooting

These are the integration errors that come up most often.

Polling too aggressively. Start at a two-second interval and double it up to a ceiling of around 30 seconds. Tight-looping the /tasks/{task-id} endpoint burns rate-limit budget and produces 429s that slow the whole pipeline down.

Treating FAILED as transient. A FAILED status means the job encountered a specific error. Read the task response body, surface the reason, and branch on it. Retrying indefinitely on FAILED produces the same failure indefinitely.

Downloading before COMPLETED. Some integrations skip the status check and call the download endpoint immediately after the operation response. The result is a partial or empty file. Always confirm status == "COMPLETED" before hitting the download endpoint.

Mixing up the three IDs. All three appear in the same code block so they can’t be confused:

upload_doc_id = upload_file("input.pdf") # documentId → input to operation endpoints

task_id = flatten(upload_doc_id) # taskId → input to the polling endpoint

result_doc_id = poll_task(task_id) # resultDocumentId → input to the download endpoint

download(result_doc_id, "output.pdf")

The download endpoint takes the resultDocumentId, not the upload documentId or the taskId.

Task status casing. The polling endpoint returns PENDING, PROCESSING, COMPLETED, and FAILED in uppercase. Branching on lowercase "completed" will silently never match and your loop will run forever.

continueMergeOnError semantics. Setting this to true lets the merge skip a failing source and continue. Setting it to false aborts the entire batch if any source fails. In production, always set this explicitly.

Retrying 4xx responses. Retry on 5xx errors and timeouts. A 400 or 401 will return the same 4xx until you fix the request, so don’t retry them.

Auth header format. client_id and client_secret are separate headers, lowercase with underscores, passed individually. They’re not concatenated, Base64-encoded, or Bearer-prefixed.

pdf-flatten does not encrypt. Flattening makes a document’s content static but doesn’t restrict access to the file. If your compliance workflow requires both, chain a pdf-protect call after the flatten step using the flatten task’s resultDocumentId as the next documentId input.

PDF Editor API FAQ

What is the Foxit PDF Services API used for?

The Foxit PDF Services API is a cloud-based REST API for programmatic PDF manipulation at scale, covering page manipulation, document merging, splitting, and annotation flattening. Any language that can send HTTP requests can use it without installing local dependencies.

How do you merge multiple PDFs using the Foxit API?

Upload each source file to get a documentId, then POST all documentIds in a documentInfos array to POST /pdf-services/api/documents/enhance/pdf-combine. Poll the returned taskId until status is COMPLETED, then download the resultDocumentId.

What is PDF flattening and when should you use it?

PDF flattening converts interactive elements (form fields, annotations, and overlays) into static page content that cannot be edited. Use it when archiving signed forms, preparing documents for print production, or meeting compliance requirements such as HIPAA that mandate immutable records at rest.

What is the difference between documentId and resultDocumentId in the Foxit API?

documentId is returned after uploading a file and is used as input to operation endpoints. resultDocumentId is returned when a task reaches COMPLETED status and is used to download the processed file. They are different identifiers; using one where the other is expected produces a 4xx error.

Does the Foxit PDF Services API support splitting PDFs by custom page ranges?

The current pdf-split endpoint splits by a fixed pageCount value, producing equal-sized chunks with the last file containing remaining pages. File-size-based and bookmark-based splitting are not available in the published API reference.

How should you handle errors in the Foxit PDF Services API?

Retry on 5xx errors and timeouts using exponential backoff. Do not retry 400 or 401 responses, since those indicate a problem with the request itself. Read the response body on FAILED task status and branch on the specific error rather than retrying blindly.

Getting Started with Foxit PDF Services API

Create a free developer account. No credit card required, and free credits are included.

Once you have your credentials, open the Foxit API Playground. Start with pdf-combine. Download input.pdf and second.pdf, upload both to get two documentIds, POST the merge request with the JSON body from the Merging section, and poll for the result. The full cycle, authentication through download, takes under ten minutes on a first attempt.

If you’re evaluating this for production volume, check the current plan options and credit pools. Plans range from the free developer tier up through Startup and Business options with larger shared-credit allocations.

For the authoritative reference on every endpoint and parameter covered in this guide, the Foxit PDF Services API documentation is your starting point. The GitHub samples repository has complete Python and Node.js examples you can clone and run immediately, including the multi-step pipeline pattern this guide covers.

Embedded Signing with the Foxit eSign API: From Envelope Creation to In-App iFrame in One Session

This guide walks through the Foxit eSign API end to end: authenticate, create a folder, generate an embedded session URL, and render the signing experience in an iFrame your users never leave.

Most embedded signing tutorials hand you a three-step abstraction: get a token, create an envelope, open a recipient view. The implementation details live somewhere else, usually mapped to a different API’s object model that doesn’t quite match what you’re working with.

This tutorial covers the Foxit eSign API embedded signing mechanics from start to finish. Authenticate once, create a “folder” (Foxit’s term for what other platforms call an envelope), receive an embedded session URL in that same response, and render it in an iFrame your users never leave. No separate field-placement API call, no client-side SDK to install.

What You’ll Build

By the end of this guide, you’ll have a working embedded signing session: a PDF loaded into your app via iFrame, signature fields defined by Text Tags, a webhook handler that verifies completion events, and a post-signing redirect that keeps users inside your product. Every step runs against the Foxit eSign sandbox with credentials you can generate in under five minutes.

1. Prerequisites and Auth Setup

Before any code runs, make sure you have the following installed and configured:

Python 3.8+
pip
venv for project isolation
The requests library
cURL
A code editor: VS Code with the Python extension is a solid choice. PyCharm, Sublime Text, and JetBrains Fleet work equally well.
A Foxit eSign developer account, available at account.foxit.com/site/sign-up with no credit card required

Set up your workspace:

mkdir foxit-esign-tutorial && cd foxit-esign-tutorial

python3 -m venv .venv && source .venv/bin/activate

pip install requests

The Foxit eSign API Is a Separate Portal from PDF Services

Developers who already use Foxit tools hit this wall first: the Foxit eSign API runs at its own base host, with its own API Key and API Secret. These credentials don’t work with the client_id and client_secret from the PDF Services developer portal at developer-api.foxit.com. The eSign documentation lives at developersguide.foxitesign.foxit.com, separate from docs.developer-api.foxit.com. The API Playground handles PDF Services sandbox testing; eSign sandbox calls go to the eSign portal directly.

The NA environment base host is https://na1.foxitesign.foxit.com. All subsequent code samples reference this as {HOST_NAME}.

Generating an OAuth 2.0 Access Token

Set your credentials as environment variables before running anything:

export FOXIT_ESIGN_CLIENT_ID="your_api_key"

export FOXIT_ESIGN_CLIENT_SECRET="your_api_secret"

Then generate a Bearer token via the OAuth 2.0 client credentials flow:

curl -X POST "https://na1.foxitesign.foxit.com/api/oauth2/access_token" \

-d "client_id=$FOXIT_ESIGN_CLIENT_ID" \

-d "client_secret=$FOXIT_ESIGN_CLIENT_SECRET" \

-d "grant_type=client_credentials" \

-d "scope=read-write"

The response carries an access_token field. Pass it as Authorization: Bearer {token} on every subsequent call, and store it server-side so your credentials never travel to the browser.

2. Creating an Envelope Programmatically with `/api/folders/createfolder`

Foxit eSign calls what other platforms call an “envelope” a folder. If you’re coming from DocuSign or PandaDoc, that naming difference will catch you on the first read of the docs. The endpoint is POST {HOST_NAME}/api/folders/createfolder. A template-based variant also exists at POST {HOST_NAME}/api/templates/createFolder (note the camelCase) for assembling envelopes from saved templates. This tutorial focuses on the direct document-upload flow.

Defining Signature Fields with Text Tags

Foxit eSign reads signature field definitions from the PDF itself at upload time. You embed them as Text Tags directly in the document, and the API parses the tags on ingest and converts them to interactive fields. The tag syntax follows this structure: ${fieldtype:party_number:required:field_name:width}. Here, y marks a field as required and n marks it as optional. The party number maps to the signing sequence for that recipient. Width is expressed as underscores.

A minimal set covering the four field types required for a real signing flow:

${s:1: } # signature field, party 1

${i:1:______} # initials field, party 1

${d:1:n::____} # optional date field, party 1

${t:1:y:Full_Name:__________} # required text field, party 1, named "Full_Name"

The full set of supported tag types includes signfield (or s), initialfield (or i), datefield (or d), textfield (or t), textboxfield (or tb), checkboxfield (or c), radiobuttonfield (or rb), securedfield (or sc), attachmentfield (or a), imagefield (or img), accept (or ab), decline (or db), payfield (or pf), and formulafield (or ff).

To hide tags in production, set the tag font color to match the page background color. Foxit eSign converts the tags to fields but does not strip them from the rendered document.

Use this sample PDF with Text Tags pre-embedded to follow along. It includes a signature field, initials, a date field, and a text input, all mapped to party 1.

Submitting the `createfolder` Request

You can supply the PDF two ways against the same endpoint. In URL mode you pass a fileUrls array of publicly reachable PDF links alongside a matching fileNames array. In base64 mode you set "inputType": "base64" and pass a base64FileString array of base64-encoded PDF bytes, again with a matching fileNames array. The API rejects a request that supplies neither, returning fileUrls or base64FileString cannot be empty.

One parameter is easy to miss and breaks the whole flow when omitted. Set processTextTags to true so the API parses the Text Tags embedded in the PDF and converts them into interactive fields. Leave it out and the folder still gets created successfully, but the tags stay inert literal text on the page, the signing UI reports zero required fields, and a signer can reach Finish without ever signing. If your source PDF carries native AcroForm fields instead of Text Tags, the companion processAcroFields flag handles those.

URL-based submission via cURL, pointing at the hosted sample PDF:

curl -X POST "https://na1.foxitesign.foxit.com/api/folders/createfolder" \

-H "Authorization: Bearer $FOXIT_ESIGN_ACCESS_TOKEN" \

-H "Content-Type: application/json" \

-d '{

"folderName": "Service Agreement",

"sendNow": false,

"processTextTags": true,

"createEmbeddedSigningSession": true,

"embeddedSignersEmailIds": ["[email protected]"],

"fileUrls": ["https://github.com/lucienchemaly/foxit-demo-templates/raw/main/esign/sample-text-tags.pdf"],

"fileNames": ["sample-text-tags.pdf"],

"parties": [

{

"firstName": "Alex",

"lastName": "Rivera",

"emailId": "[email protected]",

"permission": "FILL_FIELDS_AND_SIGN",

"sequence": 1

}

]

}'

In this request you ask Foxit eSign to fetch the tagged PDF from its public URL, hold the folder as a draft instead of emailing it by setting sendNow to false, and mint an embedded signing session for the party identified in embeddedSignersEmailIds. The single signer is defined in the parties array with a name, email, the FILL_FIELDS_AND_SIGN permission, and a signing sequence.

Base64 upload via Python, which avoids needing a public URL by sending the file bytes inline:

import os

import base64

import requests

  

HOST = "https://na1.foxitesign.foxit.com"

TOKEN = os.environ["FOXIT_ESIGN_ACCESS_TOKEN"]

  

with open("sample-text-tags.pdf", "rb") as pdf:

encoded = base64.b64encode(pdf.read()).decode()

  

payload = {

"folderName": "Service Agreement",

"sendNow": False,

"processTextTags": True,

"inputType": "base64",

"base64FileString": [encoded],

"fileNames": ["sample-text-tags.pdf"],

"createEmbeddedSigningSession": True,

"embeddedSignersEmailIds": ["[email protected]"],

# Recipient defined in the body overrides any tag-defined party

"parties": [

{

"firstName": "Alex",

"lastName": "Rivera",

"emailId": "[email protected]",

"permission": "FILL_FIELDS_AND_SIGN",

"sequence": 1,

}

],

}

  

response = requests.post(

f"{HOST}/api/folders/createfolder",

headers={"Authorization": f"Bearer {TOKEN}"},

json=payload,

)

  

print(response.json())

In this code, you read the local PDF, base64-encode its bytes, and place the result inside the base64FileString array with inputType set to base64 so the API knows to decode it rather than fetch a URL. The rest of the payload mirrors the cURL example, sending the folder as a draft and requesting an embedded session for the listed signer, after which you print the JSON response to read back the folder.folderId and the session URL. When both the PDF’s Text Tags and the API body define recipient parties, the body values take precedence, so you can reuse a tagged PDF template and swap in different signers at request time without touching the document.

3. Generating the Embedded Signing Session and Rendering the iFrame

Setting createEmbeddedSigningSession: true in the createfolder body, paired with an embeddedSignersEmailIds array naming which parties sign in your app, gives you a signed session URL in the same response. No second API call, no separate “recipient view” endpoint. The response carries an embeddedSigningSessions array, and each entry holds the signer email in emailIdOfSigner, the raw token in embeddedToken, and the ready-to-render link in embeddedSessionURL. That URL follows this format, where eetid is the URL-encoded embedded token:

https://{HOST_NAME}/embedded/embeddedsign?eetid={URL-ENCODED-EMBEDDED-TOKEN}

If you omit embeddedSignersEmailIds, the API returns email id of embedded signer(s) not submitted, so always list the embedded signers explicitly. For multi-party workflows you can set createEmbeddedSigningSessionForAllParties: true so every recipient signs in an embedded session rather than over email. When you need each signer’s live URL, request it per signer through the regenerate endpoint described below.

The full lifecycle runs from token request through webhook delivery:

Injecting the Session URL into an iFrame

The signing UI renders entirely inside the iFrame with no additional JavaScript library required.

function launchSigningSession(embeddedSessionURL) {

const iframe = document.createElement("iframe");

  

// These five sandbox permissions are the minimum required for the signing UI

iframe.setAttribute(

"sandbox",

"allow-scripts allow-same-origin allow-forms allow-popups allow-top-navigation",

);

  

iframe.src = embeddedSessionURL;

iframe.style.width = "100%";

iframe.style.height = "700px";

iframe.style.border = "none";

  

iframe.onload = function () {

console.log("Signing session ready");

};

  

document.getElementById("signing-container").appendChild(iframe);

}

The sandbox attribute matters here. Remove allow-popups or allow-top-navigation and the signing UI breaks in ways that produce no obvious error. The five attributes above are the minimum viable set. Don’t strip them without testing the complete signing flow.

To verify the flow without wiring this into your app first, download the ready-to-run iFrame test page from the demo repo, open it in a browser, paste the embeddedSessionURL from your createfolder response into the input box, and click Load. It applies the same five sandbox permissions shown above. A correctly tagged document renders with the signing controls active, as shown below.

The sample document loaded in the iFrame with processTextTags enabled. The header shows “Required Fields Left: 2” and a “Next Required Field” button, confirming the Text Tags became interactive fields. If that counter reads zero or the page shows the raw ${...} tag text with no input boxes, recheck that processTextTags was set to true on the createfolder request.

Session URLs are short-lived. Generate the URL at request time and pass it directly to the client. Don’t cache it. If a user returns to an incomplete workflow after the session expires, call POST {HOST_NAME}/api/embedded/regenerateEmbeddedSigningSession with the folder ID and the signer email to get a fresh URL. The response mirrors a single embedded session entry, returning emailIdOfSigner, embeddedToken, and the new embeddedSessionURL.

4. White-Labeling the Signing Experience

Foxit eSign exposes branding control at several levels. You can apply a custom logo to the signing UI and outgoing notification emails, set application colors to match your product’s visual design, and configure a personalized sender name so recipients see your company name rather than a generic Foxit sender identity.

For logo and color configuration, manage these settings through the eSign Portal’s branding section. The portal publishes canonical limits on file size and supported formats. Check the branding settings in your account for current specifications rather than relying on numbers printed here that may have changed.

Configuring Post-Signing Redirect URLs

Custom redirect URLs keep users inside your application after they sign, decline, defer, or hit an error. Pass them as parameters in the createfolder body:

payload = {

"folderName": "Service Agreement",

"sendNow": False,

"processTextTags": True,

"createEmbeddedSigningSession": True,

"embeddedSignersEmailIds": ["[email protected]"],

# Return the user to your confirmation page after a successful signature

"signSuccessUrl": "https://app.example.com/contracts/signed",

# Return to a dedicated page when the signer declines

"signDeclineUrl": "https://app.example.com/contracts/declined",

# Return here when the signer chooses to finish later

"signLaterUrl": "https://app.example.com/contracts/later",

# Return here if the signing session errors out

"signErrorUrl": "https://app.example.com/contracts/error",

"parties": [ ... ],

"fileUrls": [ ... ],

"fileNames": [ ... ],

}

Foxit eSign appends two query parameters to your success URL when it redirects, namely folderId for the folder that was signed and event, whose value is signing_success on a completed signature or signing_declined when the signer declines. Without these URLs, signers land on Foxit’s default confirmation page. With them, your application controls the entire post-signing navigation experience.

Tailoring Signer Instructions for Regulated Industries

Regulated workflows often need specific disclosure language in front of signers, which matters for ESIGN Act or eIDAS compliance scenarios where your legal team controls the wording. The createfolder body accepts a signerInstructionId and a confirmationInstructionId that reference instruction templates configured in your account, and you can drop explicit accept and decline button fields into the document itself using the accept (or ab) and decline (or db) Text Tag types. The eSign Developers Guide at developersguide.foxitesign.foxit.com documents these parameters.

5. Handling Webhook Callbacks for Completion Events

Foxit eSign fires HTTP POST requests to your registered endpoint when these lifecycle events occur: folder_sent, folder_viewed, folder_signed, folder_cancelled, folder_completed, folder_executed, and folder_deleted. Register your callback URL in the eSign Portal under API Settings. Make sure the endpoint is publicly reachable over HTTPS before you start testing with the sandbox.

Verifying the Webhook Signature

Every webhook POST includes a signature query parameter. It’s a base64-encoded HMAC-SHA-256 digest of the raw request body, computed using your webhook secret. Recompute the same digest server-side and compare before doing any processing. An unverified webhook is an open door.

import os

import hmac

import hashlib

import base64

from flask import Flask, request, abort

  

app = Flask(__name__)

WEBHOOK_SECRET = os.environ["FOXIT_ESIGN_WEBHOOK_SECRET"].encode()

  

@app.route("/webhook/foxit", methods=["POST"])

def foxit_webhook():

# Step 1: Pull the signature from the query string

received_sig = request.args.get("signature", "")

  

# Step 2: Recompute HMAC-SHA-256 over the raw request body

raw_body = request.get_data()

computed_sig = base64.b64encode(

hmac.new(WEBHOOK_SECRET, raw_body, hashlib.sha256).digest()

).decode()

  

# Step 3: Constant-time comparison guards against timing attacks

if not hmac.compare_digest(received_sig, computed_sig):

abort(403)

  

payload = request.json

event_name = payload.get("event_name")

folder_id = payload.get("data", {}).get("folder", {}).get("folderId")

  

if event_name in ("folder_completed", "folder_executed"):

handle_completion(folder_id)

elif event_name == "folder_cancelled":

handle_cancellation(folder_id)

  

# A non-2xx response triggers Foxit's automatic retry logic.

# Return 200 once verification and basic parsing succeed.

return "", 200

The payload structure is consistent across all events, carrying a top-level event_name, an event_date timestamp, and a data object whose folder field holds the full folder record. The folder identifier lives at data.folder.folderId, alongside the rest of the envelope-level metadata such as folderName and folderStatus.

Downstream Actions Triggered from `folder_completed`

When folder_completed or folder_executed fires, two actions cover the majority of production workflows. Fetch the signed document via the documents endpoint using the folder ID and store the result in your document storage layer. For contracts that require sequential agreements (a master services agreement followed by a statement of work, for example), fire the next createfolder call as part of the completion handler.

Audit history is available programmatically via GET {HOST_NAME}/api/folders/viewActivityHistory?folderId={FOLDER_ID}, which returns the full signing log once a folder has been shared or sent. This is a GET-only endpoint, and a folder still in DRAFT returns logs of a non-shared folder can not be viewed.

6. Common Mistakes and Troubleshooting

Text Tag Syntax Breaks on Copy-Paste

Smart-quote autocorrect in Word, Google Docs, and many other editors replaces straight ASCII brackets and quote characters with typographic equivalents. Tag parsing fails silently when this happens. Always paste tags into a plain-text editor first and verify the bracket characters are straight ASCII. The eSign Developers Guide writes every field-type notation in lowercase, such as signfield or s and textfield or t, so author your tags in lowercase to match the documented syntax rather than experimenting with capitalized variants.

Visible Text Tags Reaching Production

Foxit eSign converts embedded tags to fields but does not remove them from the document. If you ship a PDF without setting the tag text color to match the page background, signers see the raw ${...} strings on the page. Build the color-hide step into your PDF preparation pipeline before it becomes a support ticket.

Body-Level `parties` Overriding Tag-Defined Recipients

Tags define field layout and recipient assignment and must be embedded in the PDF itself, while recipient definitions in the API request body override tag-defined recipient metadata. If you’re seeing the wrong signer name or email appear, check whether a body-level parties definition is overriding the tag.

Expired Session URLs

Embedded session URLs are short-lived. Caching one and reusing it on the next page load will fail. Call POST {HOST_NAME}/api/embedded/regenerateEmbeddedSigningSession with the folder ID and signer email each time a returning user needs access to an incomplete session.

Over-Restrictive `sandbox` on the iFrame

The five required sandbox permissions are allow-scripts, allow-same-origin, allow-forms, allow-popups, and allow-top-navigation. If the UI loads but behaves unexpectedly, check your sandbox attributes first.

Credential Confusion Between eSign and PDF Services

The API Key and API Secret from the eSign Portal are specific to the eSign API, and the OAuth 2.0 flows also differ between the two. Using PDF Services credentials against the eSign /api/oauth2/access_token endpoint returns an authentication error. Keep the two credential sets separate and named clearly in your environment configuration.

Skipping Webhook Signature Verification

Always verify the signature query parameter before processing any payload. Return a 200-class status code once verification and basic parsing succeed, because a non-2xx response causes Foxit to retry delivery, which can create duplicate processing if your handler is not idempotent.

Embedded Signing FAQ

Can I regenerate an expired embedded signing session?

Yes. Call POST {HOST_NAME}/api/embedded/regenerateEmbeddedSigningSession with the folder ID and signer email. Foxit eSign returns a fresh embeddedSessionURL for the same envelope without resetting the signing state.

Do I need a separate Foxit account if I’m already using Foxit PDF Services?

Yes. The Foxit eSign API operates from a separate portal at na1.foxitesign.foxit.com with its own credentials. The two portals don’t share API keys, secrets, or authentication tokens.

Can I use an existing template instead of uploading a PDF?

Yes. Use POST {HOST_NAME}/api/templates/createFolder to assemble the envelope from a saved template rather than a raw document upload.

Does the embedded signing session work on mobile browsers?

Yes. The iFrame renders responsively on modern mobile browsers without additional configuration.

Is the audit trail accessible programmatically?

Yes. GET {HOST_NAME}/api/folders/viewActivityHistory?folderId={FOLDER_ID} returns the full signing activity log for any shared or sent envelope, including timestamps for each event. A folder still in DRAFT has no shared history to return.

What is the difference between folder_completed and folder_executed?

Both events signal that the folder has been completed with all required parties’ signatures, and the eSign Developers Guide describes them in the same terms, each delivering the folder record in data.folder. Listen for either to trigger downstream retrieval of the signed document, and make your handler idempotent so receiving both for the same folder does not double-process it.

Next Step

Activate your free Foxit eSign developer account at account.foxit.com/site/sign-up, no credit card required. Generate your OAuth token, fire a POST /api/folders/createfolder request with createEmbeddedSigningSession: true against the sandbox, and verify the returned URL loads in a local iFrame. From account creation to a working embedded signing session takes under 30 minutes.

Automating Financial Document Workflows with Foxit APIs: Generate Statements, Embed eSign, and Extract Audit-Ready Data

Learn how to automate financial services document workflows using Foxit APIs, covering quarterly statement generation, embedded eSign for account onboarding, and audit-ready PDF/A archiving with PII redaction.

The standard financial services document pipeline looks fine until a compliance audit exposes it. A templating tool generates quarterly statements. A standalone eSign vendor handles account onboarding. A manual export process (or a fragile ETL job nobody fully owns) produces the data package your audit team needs. Three vendor contracts, three auth systems, and three event logs that stop at their own API boundaries.

The more durable architecture treats document generation, e-signature orchestration, and audit-ready data extraction as a single API-backed pipeline. This article wires that pipeline together end to end, using the Foxit Document Generation API for quarterly statements, the Foxit eSign API for embedded onboarding signatures, and the Foxit PDF SDK plus Smart Redact Server for downstream extraction, PDF/A archiving, and PII scrubbing. All examples run against a free Foxit developer account.

Prerequisites

Before you run any code, get two accounts and one workspace set up.

Accounts. Create your Foxit developer account at https://account.foxit.com/site/sign-up, where activation is instant and includes free credits. Retrieve your client_id and client_secret from the Foxit Developer Portal. The eSign API runs on a different platform and requires a separate account in the Foxit eSign Portal. Activate API access under the API tab in the eSign settings menu, then fill out the form to receive your API Key and API Secret. These are not the same credentials as your DocGen account, and that distinction matters for every auth call in Section 3.

SDK and license files. If you plan to run Section 4’s PDF/A archive step, also request a Foxit PDF SDK trial through the Foxit Developer Hub. The PyPI wheel covered in Section 4 is the runtime binary your code imports, and the trial download provides gsdk_sn.txt and gsdk_key.txt, which are the credentials Library.Initialize requires. Confirm the license you receive lists Compliance on its Modules= line, since the archive step needs that module. Evaluation licenses also carry a fixed expiry window from the issue date (the distribution validated for this article was issued for a 36-day window), so request a fresh trial through the portal if yours has lapsed.

Runtime. You’ll need Python 3.8+ and cURL. Install jq if you want to inspect JSON responses inline. VS Code with the Python extension works well as a default; PyCharm and Sublime Text both work fine too.

Workspace bootstrap. Run this block to get a clean isolated environment:

mkdir foxit-financial && cd foxit-financial
python3 -m venv .venv && source .venv/bin/activate
pip install requests

Credentials. Never hardcode API keys. Set these five environment variables before running any snippet in this article:

export BASE_URL="https://na1.fusion.foxit.com"
export DOCGEN_CLIENT_ID="your_docgen_client_id"
export DOCGEN_CLIENT_SECRET="your_docgen_client_secret"
export ESIGN_API_KEY="your_esign_api_key"
export ESIGN_API_SECRET="your_esign_api_secret"

1. Why Three-Vendor Document Pipelines Break Under Compliance Pressure

The fragmentation pattern is consistent across mid-market brokerages and fintechs, where one vendor generates documents, another handles signatures, and a third (or an internal script) handles data extraction for audit packages. Each seam creates a specific compliance problem.

When a client signs their account agreement in the eSign portal, that event lives in the eSign vendor’s audit log. The generated quarterly statement lives in your templating tool’s system. The trade confirmation data lives in your data warehouse. None of these systems talk to each other by default. If an examiner asks for a unified event trail (who generated the document, who signed it, when, and where the underlying data went), you’re assembling that answer manually from three separate exports. That’s a control gap, not just an inconvenience.

There’s also a maintenance cost. Every vendor boundary means a separate OAuth2 registration, separate webhook configuration, separate error-handling logic, and separate retry strategies. When the eSign vendor rotates their API endpoint or introduces a breaking schema change, your generation pipeline doesn’t know about it. The two systems are coupled only through your code, which means you absorb every upstream change.

The architectural alternative collapses those seams. A single REST API surface covers generation (na1.fusion.foxit.com), signing (na1.foxitesign.foxit.com), archiving, and redaction. OAuth2 scopes control access at each stage. Webhooks propagate state across systems so a signature event on an account agreement can trigger downstream archival automatically, with no polling job or cron script required.

The rest of this article walks each stage of that pipeline with working code.

2. Auto-Generating Quarterly Statements with the DocGen API

Step 1: Validate Your Template with the AnalyzeDocumentBase64 Endpoint

Download the ready-to-use quarterly statement template here: quarterly_statement.docx. The template uses double-bracket text tags for flat client metadata ({{client_name}}, {{account_number}}, {{statement_period}}, {{portfolio_value}}) plus a {{TableStart:holdings}} / {{TableEnd:holdings}} loop for portfolio positions.

Before wiring up your data pipeline, call the AnalyzeDocumentBase64 endpoint to confirm the API can parse every tag. This catches naming mismatches before they produce silent blank fields in production.

curl -X POST "${BASE_URL}/document-generation/api/AnalyzeDocumentBase64" \

-H "client_id: ${DOCGEN_CLIENT_ID}" \

-H "client_secret: ${DOCGEN_CLIENT_SECRET}" \

-H "Content-Type: application/json" \

-d '{

"base64FileString": "'$(base64 -i quarterly_statement.docx)'",

"fileType": "docx"

}'

The response returns a singleTagsString (comma-separated list of scalar tags and loop column names) and a doubleTagsString (comma-separated list of loop names). For quarterly_statement.docx, the response should be {"singleTagsString":"client_name,account_number,statement_period,portfolio_value,ROW_NUMBER,symbol,quantity,marketValue","doubleTagsString":"holdings"}. Verify that every tag your data payload will populate appears in one of those two strings before you proceed. If a tag is missing, check whether Word split it across multiple text runs (see the Common Mistakes appendix).

Step 2: Generate the PDF with `GenerateDocumentBase64`

The GenerateDocumentBase64 endpoint accepts the Word template as a base64-encoded string plus a JSON data payload and returns the rendered document (also base64-encoded) in the same synchronous HTTP response. No polling required.

import os, base64, requests

  

DOCGEN_URL = "https://na1.fusion.foxit.com/document-generation/api/GenerateDocumentBase64"

CLIENT_ID = os.environ["DOCGEN_CLIENT_ID"]

CLIENT_SECRET = os.environ["DOCGEN_CLIENT_SECRET"]

  

# Load and encode the Word template

with open("quarterly_statement.docx", "rb") as f:

encoded_template = base64.b64encode(f.read()).decode()

  

# Build the data payload

payload = {

"base64FileString": encoded_template,

"fileType": "docx",

"outputFormat": "pdf",

"documentValues": {

"client_name": "Alex Rivera",

"account_number": "ACC-20241231-0042",

"statement_period": "Q4 2024",

"portfolio_value": "$248,750.00",

"holdings": [

{"symbol": "AAPL", "quantity": "50", "marketValue": "$9,100.00"},

{"symbol": "MSFT", "quantity": "30", "marketValue": "$12,360.00"},

{"symbol": "VTSAX", "quantity": "400", "marketValue": "$45,200.00"},

],

},

}

  

resp = requests.post(

DOCGEN_URL,

json=payload,

headers={

"client_id": CLIENT_ID,

"client_secret": CLIENT_SECRET,

"Content-Type": "application/json",

},

)

resp.raise_for_status()

  

# Decode and save the rendered PDF

pdf_bytes = base64.b64decode(resp.json()["base64FileString"])

with open("statement_q4_2024_rivera.pdf", "wb") as f:

f.write(pdf_bytes)

  

print(f"Generated: {len(pdf_bytes):,} bytes")

In this code, you load the Word template off disk, base64-encode it, build a documentValues dict that mirrors the template tags exactly (flat scalars for client metadata, an array of objects for the holdings loop), POST the payload to GenerateDocumentBase64, decode the base64FileString field from the JSON response back into raw PDF bytes, and persist the result. The data contract is straightforward, since flat scalar keys map to single-value tags, the holdings array of objects drives the {{TableStart:holdings}} loop, and each object in holdings needs the same keys as the column tags inside the loop (symbol, quantity, marketValue).

Step 3: Batch Generation and the 4 MB Limit

The DocGen API enforces a 4 MB cap on the base64FileString payload, measured as the base64-encoded size and not the raw .docx on disk. A 2.5 MB Word file encodes to roughly 3.3 MB in base64, which leaves little room for embedded images or fonts.

When the cap is exceeded, the API returns HTTP 500 with the plain-text body An error occurred while analyzing the template: Document file contents cannot be larger than 4 MB. To recover, slim the template. Compress images via Word’s Picture Format → Compress Pictures pane (targeting screen resolution is usually enough for PDF output), remove any embedded OLE objects, and drop embedded fonts if they aren’t required for rendering. If the template genuinely needs to stay large, split it into multiple templates and merge the rendered PDFs downstream.

For quarterly runs across thousands of accounts, parallelise POST requests against GenerateDocumentBase64 using a thread pool. The API is stateless and synchronous, so scaling means concurrent requests against your credit budget, not job-queue management.

from concurrent.futures import ThreadPoolExecutor

  

def generate_statement(client_record):

payload["documentValues"] = client_record

r = requests.post(DOCGEN_URL, json=payload, headers=headers)

r.raise_for_status()

return base64.b64decode(r.json()["base64FileString"])

  

with ThreadPoolExecutor(max_workers=10) as pool:

pdfs = list(pool.map(generate_statement, client_records))

If your batch jobs need explicit async task tracking with status polling, the Foxit PDF Services API exposes that pattern. For statement generation at quarterly cadence, the synchronous loop above is simpler and just as reliable.

3. Embedding eSign Flows for Account Onboarding

Authentication: A Separate Account on a Separate Host

The eSign API runs on na1.foxitesign.foxit.com, not the na1.fusion.foxit.com host used for DocGen. It also uses a different developer account and a different auth model. DocGen takes client_id and client_secret directly as request headers on every call. eSign requires a proper OAuth2 client_credentials exchange first, then a bearer token on subsequent calls.

Exchange your API Key and API Secret for an access token:

curl -X POST "https://na1.foxitesign.foxit.com/api/oauth2/access_token" \

-d "grant_type=client_credentials" \

-d "client_id=${ESIGN_API_KEY}" \

-d "client_secret=${ESIGN_API_SECRET}" \

-d "scope=read-write"

The response includes access_token. Pass it as Authorization: Bearer <token> on every subsequent eSign API call. Tokens expire, so cache them with their expires_in value and refresh before expiry rather than on every request.

Document Setup with Text Tag Tokens

Download the ready-to-use account agreement here: account_agreement.pdf. The document embeds signature, date, and initials fields using dollar-brace Text Tag tokens. The token format uses colon-delimited segments for field type, party number, mandatory flag, and a placeholder string.

Three tokens cover the common onboarding case:

${signfield:1:y:____} is a mandatory signature for party 1
${datefield:2:n::____} is an optional date for party 2
${i:2:n} is an optional initials field for party 2

The party number in each token drives multi-party routing automatically. Party 1 sees their signature field; party 2 sees the date and initials fields. No additional routing configuration is needed in the API call, since the document itself encodes the routing.

To create the folder and send it for signature in one call, POST to /folders/createfolder with the document URL, file name, parties array, and sendNow: true. Setting processTextTags: true instructs Foxit eSign to parse the dollar-brace tokens out of the PDF text layer and convert them into the appropriate form fields. The party fields are permission (signing role, typically FILL_FIELDS_AND_SIGN) and sequence (party order within the folder); the request schema does not use partyRole or partyNumber.

curl -X POST "https://na1.foxitesign.foxit.com/api/folders/createfolder" \

-H "Authorization: Bearer ${ACCESS_TOKEN}" \

-H "Content-Type: application/json" \

-d '{

"folderName": "Account Agreement - Alex Rivera",

"fileUrls": ["https://github.com/lucienchemaly/foxit-demo-templates/raw/main/account_agreement.pdf"],

"fileNames": ["account_agreement.pdf"],

"processTextTags": true,

"signInSequence": false,

"sendNow": true,

"parties": [

{

"firstName": "Alex",

"lastName": "Rivera",

"emailId": "[email protected]",

"permission": "FILL_FIELDS_AND_SIGN",

"sequence": 1,

"workflowSequence": 1

}

]

}'

The request above creates a draft folder for Alex Rivera, attaches the published account_agreement.pdf by URL, asks Foxit to parse the embedded Text Tag tokens, and dispatches the folder for signature in a single round trip. The folder status moves through DRAFT → SHARED → WAITING_FOR_SIGNATURE → EXECUTED as the signing process advances. If you prefer a two-step flow (create the draft, then dispatch later), POST the same body with sendNow: false to /folders/createfolder and follow up with a POST /folders/sendDraftFolder carrying the returned folderId. The webhook response uses different field names than the request for these party properties (contractPermissions, partySequence, workflowSignSequence), so map them accordingly when you persist signing events.

Webhook Integration: Seven Events, One That Matters Most for Archival

Register your callback URL in the eSign developer portal under Settings → Webhooks. The eSign API exposes seven webhook events covering the full folder lifecycle:

folder_sent, when the folder is dispatched to all parties
folder_viewed, when any party opens the folder (payload adds viewing_party)
folder_signed, when any party signs (payload adds signing_party)
folder_cancelled, when any party declines (payload adds cancelling_party and reason_for_cancelling)
folder_completed, once all required signatures are collected
folder_executed, which fires 5 to 10 seconds after folder_completed once the digital signature is applied to the completed PDF
folder_deleted, when the folder is removed (payload adds deleting_party)

Every callback POSTs a JSON body with three top-level keys (event_name, event_date in Unix milliseconds, and data). The data.folder object carries the full folder context including folderId, folderName, folderStatus, folderDocumentIds, documentsList, folderRecipientParties, and bulkId.

Hook folder_signed for per-party CRM and onboarding status updates. Hook folder_executed (not folder_completed) for archival triggers. The distinction matters, because folder_completed fires when all signatures are in but before the digital signature has been applied to the PDF, whereas folder_executed guarantees the downloaded PDF is the final, digitally signed document.

Webhook Security: HMAC on the Raw Body

Configure a Webhook Secret in the eSign API settings page. Foxit eSign computes an HMAC-SHA-256 digest of the raw HTTP request body using that secret, base64 encodes it, and appends it to your callback URL as a signature query parameter (for example, https://your-app.example.com/webhook?signature=XXXXXXXXXXXX).

Verify against the raw body bytes, not against the JSON-decoded and re-serialised payload. Any whitespace or key-ordering difference between parse and re-serialize will break the comparison.

import hmac, hashlib, base64

  

WEBHOOK_SECRET = os.environ["WEBHOOK_SECRET"]

  

def verify_webhook_signature(raw_body: bytes, signature_param: str) -> bool:

computed = base64.b64encode(

hmac.new(WEBHOOK_SECRET.encode(), raw_body, hashlib.sha256).digest()

).decode()

return hmac.compare_digest(computed, signature_param)

  

# In your Flask/FastAPI handler:

  

# raw_body = await request.body() # capture before any parsing

  

# sig = request.query_params["signature"]

  

# if not verify_webhook_signature(raw_body, sig):

  

# return Response(status_code=403)

Rotate the Webhook Secret through the API settings page immediately if it leaks.

Bulk Dispatch for High-Volume Onboarding Campaigns

For campaigns where you’re sending the same agreement to a large group, set partyIsEmailGroup: true on the relevant party in your createfolder body and provide an emailGroupId (the ID of the email group configured in your eSign account). When partyIsEmailGroup is true, the firstName, lastName, and emailId fields on that party are ignored, and the group definition drives the recipients. Set allowSingleSignerInBulk: true if only one member of the group needs to sign to complete the folder. The folder response includes a bulkId field that identifies the bulk run (0 for non-bulk sends).

For onboarding flows that require one personalised folder per recipient (different client data, different document content), parallelise calls to /folders/createfolder from a worker pool sized to your credit budget. No single-call endpoint generates thousands of personalised folders in one shot.

4. Extracting Audit-Ready Data for Financial Document Workflows

Server-Side Text and Table Extraction with the PDF SDK

The Foxit PDF SDK handles programmatic text and table extraction server-side, which eliminates the manual export step that breaks most audit pipelines. Install the Python wrapper from PyPI for the compiled runtime binary (arm64 macOS, x64 Linux, and x64 Windows wheels are published):

pip install FoxitPDFSDKPython3

The PyPI wheel ships the runtime binary only. To obtain the serial number and license key that Library.Initialize requires, request a trial through the Foxit Developer Hub and read gsdk_sn.txt and gsdk_key.txt from the unpacked archive. Foxit evaluation licenses are bound to the SDK distribution they ship alongside, so request the trial through the route you actually plan to run. The PyPI wheel needs a license issued for it, not one extracted from the legacy x86_64 macOS download (that bundle is x86_64-only and was built against Python 2, which is incompatible with both arm64 Apple Silicon hosts and modern Python 3 runtimes).

The SDK supports text extraction at the page level and table detection from structured content, which is useful for pulling portfolio positions, transaction histories, and account summaries into JSON before writing to an audit package or data warehouse.

PDF/A Conversion: Convert, Then Verify, Then Reject on Failure

Generated and signed documents need to pass through the Foxit PDF SDK PDF/A Compliance add-on before archiving. The Python binding flattens the underlying C++ namespaces, so the PDFACompliance class lives directly on the top-level FoxitPDFSDKPython3 module (not under a nested addon submodule). It exposes two main methods, namely ConvertPDFFile() to produce a compliant output and Verify() to check an existing PDF against a target version. Initialize the SDK once at process start via foxit.Library.Initialize(sn, key) (the call returns an int error code, not an exception), then boot the ComplianceEngine before instantiating PDFACompliance.

Pull the values for FOXIT_SDK_SN and FOXIT_SDK_KEY from the SDK trial download referenced in the prerequisites. gsdk_sn.txt ships as a single line of the form SN=<value>, and the literal SN= prefix must be stripped before the value is exported (passing the whole line yields e_ErrInvalidLicense from a key that would otherwise work). gsdk_key.txt is an INI-style file starting with [Foxit SDK License], and the value passed to Library.Initialize is only the contents of the Sign= line (the long base64 blob), not the full INI file. Passing the full file yields e_ErrInvalidLicense even with the correct SN. ComplianceEngine.Initialize takes the path to the compliance resource folder as its first argument, and the second argument is the engine unlock code (an empty string for trial keys). The resource folder is the res/ directory inside the SDK trial download; point FOXIT_COMPLIANCE_RESOURCE_FOLDER at that path.

The version enums are direct class attributes (no PDFACompliance.Version sub-namespace). Supported versions span PDF/A-1 through PDF/A-3, including e_VersionPDFA1a, e_VersionPDFA1b, e_VersionPDFA2a, e_VersionPDFA2b, e_VersionPDFA2u, e_VersionPDFA3a, e_VersionPDFA3b, and e_VersionPDFA3u, aligned with ISO 19005-1, 19005-2, and 19005-3. PDF/A-4 (ISO 19005-4) is not in the enum and is not supported.

import os

import logging

import FoxitPDFSDKPython3 as foxit

  

logger = logging.getLogger(__name__)

  

SDK_SN = os.environ["FOXIT_SDK_SN"]

SDK_KEY = os.environ["FOXIT_SDK_KEY"]

COMPLIANCE_RESOURCE_FOLDER = os.environ["FOXIT_COMPLIANCE_RESOURCE_FOLDER"]

  

err = foxit.Library.Initialize(SDK_SN, SDK_KEY)

if err != foxit.e_ErrSuccess:

raise RuntimeError(f"Foxit SDK Library.Initialize failed with code {err}")

  

# Second argument is the engine unlock code; trial keys use the empty string.

err = foxit.ComplianceEngine.Initialize(COMPLIANCE_RESOURCE_FOLDER, "")

if err != foxit.e_ErrSuccess:

raise RuntimeError(f"Foxit ComplianceEngine.Initialize failed with code {err}")

  

def archive_as_pdfa(src_path: str, dest_path: str) -> bool:

pdfa = foxit.PDFACompliance()

  

# Convert to PDF/A-2b (ISO 19005-2, Level B)

convert_result = pdfa.ConvertPDFFile(

src_path,

dest_path,

foxit.PDFACompliance.e_VersionPDFA2b,

None,

)

if not convert_result.IsEmpty():

# Non-empty ResultInformation means the conversion surfaced

# unresolved compliance issues.

logger.error(

"PDF/A conversion left %d unresolved issues for %s",

convert_result.GetHitDataCount(),

src_path,

)

return False

  

# Verify the output, since silent failure on non-compliant input is the SDK default.

# Signature: Verify(version_enum, file_path, start_page, end_page, progress_callback).

verify_result = pdfa.Verify(

foxit.PDFACompliance.e_VersionPDFA2b,

dest_path,

0,

-1,

None,

)

if not verify_result.IsEmpty():

logger.error(

"PDF/A verification found %d violations in %s",

verify_result.GetHitDataCount(),

dest_path,

)

return False

  

return True

The code initializes the SDK with Library.Initialize (the v11.1.0 Python binding’s entry point), boots the ComplianceEngine, converts the source PDF to PDF/A-2b, and verifies the output. Both ConvertPDFFile() and Verify() return a ResultInformation object, and an empty result (IsEmpty() == True) indicates a clean run with no unresolved compliance issues. Log non-empty results explicitly with the hit count from GetHitDataCount(), because a non-compliant PDF passed silently to your archive is exactly the gap that surfaces during an SEC or FINRA examination.

PII Scrubbing Before Audit Delivery

Route documents through Foxit Smart Redact Server as a pipeline stage before external delivery or third-party audit access. AI-assisted detection identifies SSNs, account numbers, credit card numbers, names, emails, and phone numbers across 47+ supported file types, including PDF, Word, Excel, HTML, JSON, and XML.

Smart Redact Server protects documents with AES-256 encryption at rest and SSL 2048-bit encryption in transit. It operates under a zero data retention policy, so originals and intermediate files are deleted after processing. The Smart Redact Security and Privacy page documents one nuance, where sensitive findings may be stored in encrypted form for follow-up review actions even though the source document itself is not retained. Wire Smart Redact as the final stage before delivery, not as an afterthought applied to a subset of documents.

5. Compliance Controls You Can Actually Audit

Audit Trail Coverage

The eSign API captures a timestamped event log for every signing action, including who signed, when, from what IP address, and with what authentication method. These events are accessible programmatically through the API, not just through the portal UI. That means you can pipe signing events directly into your SIEM or compliance reporting system without manual exports. The folder_signed webhook event delivers enough detail per party to satisfy most per-transaction audit requirements.

Encryption and Access Control

Every Foxit API tier in this pipeline shares the same encryption posture, with TLS 1.2 or higher in transit and AES-256 at rest. The Foxit API Security and Compliance page documents this posture for both the eSign API and the PDF Services/Embed APIs (which covers the DocGen endpoints used in Section 2), alongside SOC 2 Type II certification, segmented customer data at rest, and HIPAA BAA availability.

OAuth2 scopes control which services can read, write, or execute at each pipeline stage. Structure scope grants to enforce least-privilege access between your generation, signing, and archiving services. A job that only reads signed documents shouldn’t hold a read-write token for the generation endpoint.

Retention and Purge

The eSign API supports applying retention rules and triggering purges of outdated records programmatically. For FINRA Rule 4511 and SEC Rule 17a-4 compliance, you need both provable retention (records preserved for the required period) and provable deletion (records removed at end of retention). An API-driven purge that produces a deletion receipt is far easier to defend in an examination than a manual deletion from a portal UI.

6. Start with the Statement Generation Pipeline Today

The fastest way to harden your financial document workflows is to wire the statement generation stage first and let the rest of the pipeline follow. Create a free developer account at https://account.foxit.com/site/sign-up; no credit card is required and activation is instant. Retrieve your client_id and client_secret from the Foxit Developer Portal.

Download the Postman collection from the developer portal, load the AnalyzeDocumentBase64 request, attach quarterly_statement.docx, and fire it. The response lists every detected placeholder, so you can confirm tag names match your data schema before writing a single line of integration code.

Take the tag list from the Analyze response, construct a minimal JSON payload with one client record, POST it to GenerateDocumentBase64, and verify the PDF output renders locally. Once that loop closes, you have a working proof of concept for the statement generation stage, and the rest of the pipeline follows the same pattern.

Appendix: Common Mistakes

DocGen and eSign use different auth models. DocGen takes client_id and client_secret as headers on every request. eSign requires the OAuth2 client_credentials exchange against /api/oauth2/access_token first, then a bearer token on subsequent calls. They’re different accounts in different portals.

Word’s autocorrect splits tags typed character-by-character across runs. This makes the placeholder unparseable and renders a blank field. Always paste tags in as plain text, then verify with Show/Hide formatting marks (¶).

Smart quotes inside format strings render blank. Disable smart quotes in AutoCorrect Options before authoring the template. A format tag like {{portfolio_value # "$#,##0.00"}} breaks silently if Word replaces the double quotes with curly equivalents.

TableStart and TableEnd for the same array must sit in cells of the same row of the same Word table. Different rows or different tables produce a 400 or a silent blank.

HTTP 500 with the body Document file contents cannot be larger than 4 MB means the base64-encoded .docx exceeded the DocGen 4 MB cap. Slim the template per the Section 2 guidance.

Webhook HMAC verification must run on the raw body bytes, not the parsed JSON. Whitespace normalisation or key-ordering changes between receipt and re-serialisation break the comparison. Capture request.body() before any parsing.

folder_executed is the correct archival hook, not folder_completed. folder_completed fires when all required signatures are collected, but the digital signature hasn’t been applied to the PDF yet. folder_executed fires 5 to 10 seconds later once the digital signature is embedded, and that’s the download-ready version.

Do not claim PDF/A-4 support. The PDFACompliance version enum covers PDF/A-1 (a, b), PDF/A-2 (a, b, u), and PDF/A-3 (a, b, u) only, aligned with ISO 19005-1/2/3. Always branch on the ResultInformation return value, since the SDK does not raise on non-compliant input.

Financial Services Document Automation FAQ

What is document automation for financial services?

Document automation for financial services is the use of APIs to programmatically generate, sign, and archive client-facing documents like quarterly statements, account agreements, and compliance disclosures without manual intervention. Rather than stitching together separate tools for each stage, a unified API pipeline handles the full lifecycle from template rendering through audit-ready archival, reducing vendor fragmentation and closing compliance control gaps.

How does the Foxit DocGen API generate quarterly statements?

The Foxit DocGen API accepts a Word template with double-bracket tags (e.g. {{client_name}}, {{TableStart:holdings}}) and a JSON data payload, then returns a rendered PDF in the same synchronous HTTP response with no polling required. You call AnalyzeDocumentBase64 first to validate every template tag against your data schema, then GenerateDocumentBase64 with your client record to produce the statement. The API enforces a 4 MB cap on the base64-encoded template payload.

What is the difference between folder_completed and folder_executed in the Foxit eSign API?

folder_completed fires once all required signatures are collected, but before the digital signature has been applied to the PDF. folder_executed fires 5 to 10 seconds later, once the digital signature is embedded and the document is finalized. For archival triggers in financial workflows where you need the legally binding, digitally signed version, folder_executed is the correct webhook event to hook, not folder_completed.

How do you verify Foxit eSign webhook authenticity?

Foxit eSign computes an HMAC-SHA-256 digest of the raw HTTP request body using your configured Webhook Secret, base64-encodes it, and appends it to your callback URL as a signature query parameter. Verification must run against the raw body bytes before any JSON parsing, because whitespace normalization or key-reordering during parse and re-serialization will break the comparison. Use hmac.compare_digest() for a timing-safe check.

Which PDF/A versions does the Foxit PDF SDK support for financial document archiving?

The Foxit PDF SDK PDFACompliance class supports PDF/A-1 (a, b), PDF/A-2 (a, b, u), and PDF/A-3 (a, b, u), aligned with ISO 19005-1, 19005-2, and 19005-3. PDF/A-4 is not supported. For SEC Rule 17a-4 and FINRA Rule 4511 compliance, PDF/A-2b is the recommended target. Always call Verify() after ConvertPDFFile() because the SDK does not raise an exception on non-compliant input; it returns a ResultInformation object you must explicitly check.

DOCX to PDF via the Foxit PDF Services API: Python and cURL Walkthrough

This walkthrough covers the full DOCX-to-PDF flow on the Foxit PDF Services API with runnable Python and cURL for each call.

Automated document pipelines demand conversion tooling that accepts a file, queues a job, and returns clear status at every step. The Foxit PDF Services API gives you exactly that: a four-endpoint async flow covering upload, convert, poll, and download. Each step returns a typed payload, the task model exposes four explicit states with a numeric progress field, and error codes map cleanly to distinct recovery paths.

This tutorial walks through every step of that flow in Python 3 with the requests library, plus cURL equivalents for each call. You’ll have a runnable convert.py script you can drop into a pipeline today.

Prerequisites

Before you run a single line of this tutorial, get the following in place. Each item links to its canonical install or setup guide.

Python 3.8 or newer — verify with python3 --version. The script uses only standard library modules plus one external package, so any modern 3.x will do.
pip — bundled with Python 3.4+. Verify with python3 -m pip --version.
A virtual environment — isolates project dependencies so they don’t collide with system Python or other projects. See the venv tutorial for platform-specific activation commands.
The requests library — the only third-party dependency in this walkthrough. Installed inside the venv below.
A code editor — Visual Studio Code with the Python extension is a solid default, but PyCharm, Sublime Text, or any editor you like will work.
cURL — pre-installed on macOS and most Linux distros. Windows users can install from the official site or use WSL.
A Foxit Developer account — register for free (no credit card required). The Foxit Developer Portal provisions a default application with your CLIENT_ID and CLIENT_SECRET immediately after signup.

Set up the project workspace:

mkdir foxit-docx-to-pdf && cd foxit-docx-to-pdf
python3 -m venv .venv
source .venv/bin/activate   # Windows: .venv\Scripts\activate
pip install requests

Export your credentials as environment variables so the script never sees them as hardcoded strings:

export CLIENT_ID=your_client_id_here
export CLIENT_SECRET=your_client_secret_here

Your Python script reads them with `os.environ.get()`:

import os

CLIENT_ID = os.environ.get("CLIENT_ID")
CLIENT_SECRET = os.environ.get("CLIENT_SECRET")

BASE_URL = "https://na1.fusion.foxit.com"

All four API calls go to https://na1.fusion.foxit.com. The developer portal also offers a live sandbox and pre-built Postman collections if you want to verify calls in a GUI before scripting.

For a sample DOCX to work with right away, download input.docx directly from the foxitsoftware/developerapidemos GitHub repository and save it to your working directory.

How the Auth Model Works

The Foxit PDF Services API authenticates through named request headers. Pass client_id and client_secret directly on every call:

headers = {
    "client_id": CLIENT_ID,
    "client_secret": CLIENT_SECRET,
}

That single dict covers upload (multipart POST), polling (GET), and download (GET). The convert endpoint takes a JSON body, so it requires `Content-Type: application/json` as well:

json_headers = {
    "client_id": CLIENT_ID,
    "client_secret": CLIENT_SECRET,
    "Content-Type": "application/json",
}

The API expects the raw key/secret pair in those named headers. Wrapping credentials in an Authorization: Bearer header instead returns 400, since the required client_id and client_secret headers are missing.

Step 1 and Step 2: Upload the DOCX and Initiate Conversion

Step 1: Upload the DOCX File

POST /pdf-services/api/documents/upload accepts the file as multipart/form-data and returns a documentId that every subsequent call needs.

import requests

def upload_doc(file_path: str) -> str:
    url = f"{BASE_URL}/pdf-services/api/documents/upload"
    headers = {
        "client_id": CLIENT_ID,
        "client_secret": CLIENT_SECRET,
    }
    with open(file_path, "rb") as f:
        files = {"file": (os.path.basename(file_path), f)}
        response = requests.post(url, headers=headers, files=files)
    response.raise_for_status()
    return response.json()["documentId"]

cURL equivalent:

curl -X POST "https://na1.fusion.foxit.com/pdf-services/api/documents/upload" \
  -H "client_id: $CLIENT_ID" \
  -H "client_secret: $CLIENT_SECRET" \
  -F "[email protected]"

Uploaded files carry a 100 MB cap and are automatically deleted after 24 hours. A documentId scopes to the current upload session and expires with the source file, so treat it as ephemeral.

Step 2: Initiate the PDF Conversion

POST /pdf-services/api/documents/create/pdf-from-word accepts a JSON body with the documentId and returns a taskId. The API handles 10 to 10,000+ conversions per day across production pipelines, queuing jobs asynchronously to avoid blocking the connection until the PDF is ready.

import json

def convert_to_pdf(document_id: str) -> str:
    url = f"{BASE_URL}/pdf-services/api/documents/create/pdf-from-word"
    headers = {
        "client_id": CLIENT_ID,
        "client_secret": CLIENT_SECRET,
        "Content-Type": "application/json",
    }
    payload = {"documentId": document_id}
    response = requests.post(url, headers=headers, data=json.dumps(payload))
    response.raise_for_status()
    return response.json()["taskId"]

cURL equivalent:

curl -X POST "https://na1.fusion.foxit.com/pdf-services/api/documents/create/pdf-from-word" \
  -H "client_id: $CLIENT_ID" \
  -H "client_secret: $CLIENT_SECRET" \
  -H "Content-Type: application/json" \
  -d '{"documentId": "<your_document_id>"}'

The endpoint returns 202 Accepted, confirming the job is queued. It also accepts .doc, .rtf, .dot, .dotx, .docm, .dotm, and .wpd files through the same documentId input, so legacy Word formats work through the same pipeline.

Step 3: Polling the Task Status

GET /pdf-services/api/tasks/{task-id} returns four fields you need to act on in your polling loop:

status: one of PENDING, IN_PROGRESS, COMPLETED, or FAILED
progress: int32, 0 to 100
resultDocumentId: populated when status reaches COMPLETED
error: populated when status reaches FAILED

The task state machine advances in one direction: PENDING to IN_PROGRESS, then to either COMPLETED or FAILED.

import time

def poll_task(task_id: str, max_attempts: int = 30) -> str:
    url = f"{BASE_URL}/pdf-services/api/tasks/{task_id}"
    headers = {
        "client_id": CLIENT_ID,
        "client_secret": CLIENT_SECRET,
    }
    for attempt in range(max_attempts):
        response = requests.get(url, headers=headers)
        response.raise_for_status()
        data = response.json()
        status = data.get("status")
        progress = data.get("progress", 0)
        print(f"Attempt {attempt + 1}: status={status}, progress={progress}%")
        if status == "COMPLETED":
            return data["resultDocumentId"]
        if status == "FAILED":
            raise RuntimeError(f"Conversion failed: {data.get('error')}")
        time.sleep(2)
    raise TimeoutError(f"Task {task_id} did not complete in {max_attempts} attempts")

Two-second polling intervals work across a wide range of document sizes, and polling more aggressively only consumes rate limit budget without affecting conversion time.

Step 4: Downloading the Converted PDF

GET /pdf-services/api/documents/{documentId}/download fetches the finished PDF. The path parameter in the API reference reads {documentId}, but the value you pass here is the resultDocumentId from the completed poll response. The server assigns that ID to the generated PDF output at conversion time, making it the correct identifier to use at this step.

Stream the response to disk with stream=True and iter_content(chunk_size=8192). Buffering a large PDF fully into memory before writing it causes problems on high-volume pipelines.

def download_result(result_document_id: str, output_path: str) -> None:
    url = f"{BASE_URL}/pdf-services/api/documents/{result_document_id}/download"
    headers = {
        "client_id": CLIENT_ID,
        "client_secret": CLIENT_SECRET,
    }
    with requests.get(url, headers=headers, stream=True) as response:
        response.raise_for_status()
        with open(output_path, "wb") as f:
            for chunk in response.iter_content(chunk_size=8192):
                if chunk:
                    f.write(chunk)

The cURL equivalent uses the --output flag to write directly to disk:

curl -X GET "https://na1.fusion.foxit.com/pdf-services/api/documents/<result_document_id>/download" \
  -H "client_id: $CLIENT_ID" \
  -H "client_secret: $CLIENT_SECRET" \
  --output output.pdf

To verify the output, check response.headers.get("Content-Type") for application/pdf, or inspect the first four bytes of the written file for the %PDF magic bytes if your pipeline requires format validation.

Error Handling for Production

The Foxit PDF Services API documentation covers 400, 404, 413, and 500 across the four endpoints. The 401 appears on authentication failures as a practical case even though it’s absent from the documented example responses. Each status code points to a specific root cause with a concrete recovery path:

400: malformed request body or unsupported file type. Validate the input file path and extension before calling upload_doc().
401: credential misconfiguration. Verify that CLIENT_ID and CLIENT_SECRET are exported in your shell and that the header names are lowercase client_id and client_secret.
404: the documentId has expired. The server deletes uploaded files after 24 hours, so the convert and download endpoints return 404 for any documentId past that window. Re-upload the source file and restart from the upload step. An expired or unknown taskId on the poll endpoint behaves differently: it returns HTTP 200 with status: "FAILED" and an error object whose message reads "task is not exist". The poll loop’s FAILED branch already catches that case.
413: file exceeds the 100 MB upload cap. Pre-check with os.path.getsize() before uploading, or split the document.
500: transient server error. Apply exponential backoff with a ceiling of 3 retries (wait times of 1s, 2s, and 4s).

def call_with_retry(fn, *args, max_retries: int = 3, **kwargs):
    for attempt in range(max_retries + 1):
        try:
            return fn(*args, **kwargs)
        except requests.HTTPError as e:
            code = e.response.status_code
            if code == 400:
                raise ValueError(
                    "Bad request. Confirm the input is a supported Word format."
                ) from e
            if code == 401:
                raise PermissionError(
                    "Authentication failed. Check CLIENT_ID and CLIENT_SECRET env vars."
                ) from e
            if code == 404:
                raise FileNotFoundError(
                    "Document or task expired (24h TTL). Re-upload and retry."
                ) from e
            if code == 413:
                raise OverflowError(
                    "File too large. The upload cap is 100 MB."
                ) from e
            if code == 500 and attempt < max_retries:
                wait = 2 ** attempt  # 1s, 2s, 4s
                print(f"Server error. Retrying in {wait}s ({attempt + 1}/{max_retries})")
                import time
                time.sleep(wait)
                continue
            raise

Pipeline authors should treat documentId values as ephemeral: each one expires with its source file after 24 hours, so pipeline code that caches documentId values between sessions will see 404s on every convert call, and re-uploading is always the correct recovery path.

The Complete Script

Set your environment variables, then run python convert.py input.docx output.pdf:

import os
import json
import time
import sys
import requests

CLIENT_ID = os.environ.get("CLIENT_ID")
CLIENT_SECRET = os.environ.get("CLIENT_SECRET")
BASE_URL = "https://na1.fusion.foxit.com"


def call_with_retry(fn, *args, max_retries: int = 3, **kwargs):
    for attempt in range(max_retries + 1):
        try:
            return fn(*args, **kwargs)
        except requests.HTTPError as e:
            code = e.response.status_code
            if code == 400:
                raise ValueError(
                    "Bad request. Confirm the input is a supported Word format."
                ) from e
            if code == 401:
                raise PermissionError(
                    "Authentication failed. Check CLIENT_ID and CLIENT_SECRET env vars."
                ) from e
            if code == 404:
                raise FileNotFoundError(
                    "Document or task expired (24h TTL). Re-upload and retry."
                ) from e
            if code == 413:
                raise OverflowError(
                    "File too large. The upload cap is 100 MB."
                ) from e
            if code == 500 and attempt < max_retries:
                wait = 2 ** attempt  # 1s, 2s, 4s
                print(f"Server error. Retrying in {wait}s ({attempt + 1}/{max_retries})")
                time.sleep(wait)
                continue
            raise


def upload_doc(file_path: str) -> str:
    url = f"{BASE_URL}/pdf-services/api/documents/upload"
    headers = {"client_id": CLIENT_ID, "client_secret": CLIENT_SECRET}
    with open(file_path, "rb") as f:
        files = {"file": (os.path.basename(file_path), f)}
        r = requests.post(url, headers=headers, files=files)
    r.raise_for_status()
    return r.json()["documentId"]


def convert_to_pdf(document_id: str) -> str:
    url = f"{BASE_URL}/pdf-services/api/documents/create/pdf-from-word"
    headers = {
        "client_id": CLIENT_ID,
        "client_secret": CLIENT_SECRET,
        "Content-Type": "application/json",
    }
    r = requests.post(url, headers=headers, data=json.dumps({"documentId": document_id}))
    r.raise_for_status()
    return r.json()["taskId"]


def poll_task(task_id: str, max_attempts: int = 30) -> str:
    url = f"{BASE_URL}/pdf-services/api/tasks/{task_id}"
    headers = {"client_id": CLIENT_ID, "client_secret": CLIENT_SECRET}
    for attempt in range(max_attempts):
        r = requests.get(url, headers=headers)
        r.raise_for_status()
        data = r.json()
        status = data.get("status")
        print(f"[{attempt + 1}/{max_attempts}] status={status}, progress={data.get('progress', 0)}%")
        if status == "COMPLETED":
            return data["resultDocumentId"]
        if status == "FAILED":
            raise RuntimeError(f"Conversion failed: {data.get('error')}")
        time.sleep(2)
    raise TimeoutError(f"Task {task_id} did not complete after {max_attempts} attempts")


def download_result(result_document_id: str, output_path: str) -> None:
    url = f"{BASE_URL}/pdf-services/api/documents/{result_document_id}/download"
    headers = {"client_id": CLIENT_ID, "client_secret": CLIENT_SECRET}
    with requests.get(url, headers=headers, stream=True) as r:
        r.raise_for_status()
        with open(output_path, "wb") as f:
            for chunk in r.iter_content(chunk_size=8192):
                if chunk:
                    f.write(chunk)


def convert_docx_to_pdf(input_path: str, output_path: str) -> None:
    print(f"Uploading {input_path}...")
    document_id = call_with_retry(upload_doc, input_path)
    print(f"Uploaded. documentId={document_id}")

    print("Initiating conversion...")
    task_id = call_with_retry(convert_to_pdf, document_id)
    print(f"Queued. taskId={task_id}")

    print("Polling for completion...")
    result_document_id = call_with_retry(poll_task, task_id)
    print(f"Completed. resultDocumentId={result_document_id}")

    print(f"Downloading to {output_path}...")
    call_with_retry(download_result, result_document_id, output_path)
    print("Done.")


if __name__ == "__main__":
    if len(sys.argv) != 3:
        print("Usage: python convert.py <input.docx> <output.pdf>")
        sys.exit(1)
    convert_docx_to_pdf(sys.argv[1], sys.argv[2])

The Foxit PDF Services API also supports merging, compression, linearization, and OCR through additional endpoints. All of them share the same host and header-based auth pattern, so the functions you’ve built here extend naturally as your pipeline grows.

Create your free Foxit developer account and run your first conversion in under five minutes, with no credit card required at signup.

DOCX to PDF API FAQ

Does the Foxit PDF Services API support formats other than .docx?

Yes. The /pdf-services/api/documents/create/pdf-from-word endpoint accepts .doc, .docx, .rtf, .dot, .dotx, .docm, .dotm, and .wpd. The same four-step flow applies for all of them.

How long are uploaded files retained?

Uploaded documents are automatically deleted after 24 hours. Treat documentId values as ephemeral and re-upload whenever you need to convert a file after that window.

What happens if I poll the task endpoint faster than every 2 seconds?

Faster polling consumes rate limit budget without affecting conversion speed. The server determines conversion time based on document complexity and queue load, so polling intervals below 2 seconds add no throughput benefit.

Can I run multiple DOCX-to-PDF conversions in parallel?

Yes. Each upload returns an independent documentId and each conversion returns an independent taskId. Run concurrent conversions by launching multiple threads or async tasks, with each one tracking its own taskId. Python’s concurrent.futures.ThreadPoolExecutor is a straightforward way to manage this.

Where do I get my CLIENT_ID and CLIENT_SECRET?

From the Foxit Developer Portal dashboard, under the default application created at signup. Both values are available immediately after account creation.

Does the API require an OAuth token exchange?

The API authenticates through named request headers. Pass client_id and client_secret directly on every request, and the server reads those credentials on each call.

Author: Albano Moura

What an eSignature API is and how signing workflows work

Prerequisites

Step 1: Authenticate with the Foxit eSign API

Step 2: Prepare a document and define signature fields with Text Tags

Step 3: Send the document and mint an embedded session

Step 4: Render the signing session in your app

Step 5: Confirm completion with webhooks

Step 6: Retrieve the executed document and its audit trail

Common mistakes

eSignature API FAQ

Wrapping up

Prerequisites

How the Power Automate Foxit API Integration Works: Two APIs, Two Hosts, Two Flows

Step 1: CRM Trigger, Firing the Flow on a Closed Deal

Step 2: Generate the Contract PDF with GenerateDocumentBase64

Step 3: Send for Signature with OAuth2 and createfolder

Step 4: Receive the Webhook and Archive the Signed Document

Common Mistakes

API Workflow Automation FAQ

Next Step

Architecture Overview: Two Ways to Build the Same Pipeline

Step 1: Credentials and Template Prep

Step 2: CRM Webhook to DocGen, Generating the Contract

Step 3: Routing the PDF into eSign

Step 4: eSign Completion Webhook and Archive

The Vercel Workflows Alternative

CRM-Triggered Document Pipeline FAQ

Test End-to-End and Harden for Production

A Continuous Chain of REST Calls

Run n8n Locally and Get Foxit Credentials

Install Docker

Start n8n and create your local account

Get your Foxit credentials

Store the DocGen credentials once, reuse them everywhere

Import the Finished Workflow (Optional Shortcut)

Step 1: Trigger the Workflow and Generate the PDF

Add the trigger and fire it with a test request

Prepare the Word template

Add and configure the Generate PDF node

Step 2: Exchange an eSign Token and Send for Signature

Get a bearer token

Place signature fields with Text Tags

Add the Create Signature Folder node

Step 3: Capture Signing Status and Archive the Document

Common Mistakes and Troubleshooting

Foxit API n8n FAQ

What to Build Next

What You Need Before You Start

What “Agentic” Actually Means for Document Workflows

Architecture Overview: Two Modes for Agent-Driven PDF Processing

Setting Up the Foxit MCP Server

Mode 1: Programmatic Pipeline Setup

Mode 2: In-App Orchestration Setup

Core Document Operations Agents Can Execute

Agent-Triggered Signing Workflows via the eSign API

Production Considerations: Compliance, Cost, and Error Handling

Common Mistakes

Agentic Document Workflows FAQ

Start Building: Free Developer Access in Minutes

Before You Start

Prerequisites

Designing Your Invoice Word Template

Structuring Your Invoice Data as JSON

Calling the Document Generation API with Python

Generate Invoice PDF API FAQ

Next Steps

What Is the Foxit PDF Services API?

Why Backend PDF Editing Is an Infrastructure Decision

Prerequisites

Authentication and the Upload → Task → Poll → Download Loop

Authentication

The Four-Step Loop

Page Manipulation: Move, Rotate, Delete, and Add Pages

MOVE_PAGES

ROTATE_PAGES

DELETE_PAGES

ADD_PAGES

Merging and Splitting PDFs

Merging Multiple PDFs with pdf-combine

2. Creating an Envelope Programmatically with `/api/folders/createfolder`

Submitting the `createfolder` Request

Downstream Actions Triggered from `folder_completed`

Body-Level `parties` Overriding Tag-Defined Recipients

Over-Restrictive `sandbox` on the iFrame

Step 2: Generate the PDF with `GenerateDocumentBase64`