How to integrate Docuseal MCP with LangChain

This guide walks you through connecting Docuseal to LangChain using the Composio tool router. By the end, you'll have a working Docuseal agent that can list all document templates in your account, create a new template from html content, start a signature workflow from a pdf file through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Docuseal account through Composio's Docuseal MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Docuseal is an eSignature platform that lets you automate document signing and workflow management via API. Enjoy seamless, code-friendly access to digital signatures and templates without the manual hassle.

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Introduction

This guide walks you through connecting Docuseal to LangChain using the Composio tool router. By the end, you'll have a working Docuseal agent that can list all document templates in your account, create a new template from html content, start a signature workflow from a pdf file through natural language commands.

This guide will help you understand how to give your LangChain agent real control over a Docuseal account through Composio's Docuseal MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Docuseal with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Docuseal project to Composio
  • Create a Tool Router MCP session for Docuseal
  • Initialize an MCP client and retrieve Docuseal tools
  • Build a LangChain agent that can interact with Docuseal
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

What is the Docuseal MCP server, and what's possible with it?

The Docuseal MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Docuseal account. It provides structured and secure access to your eSignature workflows, so your agent can manage templates, automate document submissions, handle submitters, and streamline template operations for you.

  • Seamless template management: Effortlessly list, retrieve, update, archive, clone, or merge document templates, making it easy to organize and reuse signature documents.
  • Automated submission workflows: Instantly create new submissions from uploaded PDFs, initiate signature processes, and keep tabs on all current and past document submissions.
  • Direct HTML-to-template creation: Enable your agent to generate reusable document templates straight from HTML content—no manual web interface required.
  • Submitter roster management: Retrieve comprehensive lists of all document submitters for reporting, tracking, or management purposes with a single request.
  • Template merging and duplication: Combine multiple templates into a single document or duplicate templates to accelerate document preparation for recurring workflows.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step10 STEPS
1

Prerequisites

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • @composio/langchain provides Composio integration for LangChain
  • @langchain/mcp-adapters enables MCP client connections
  • @langchain/core is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models
5

Import dependencies

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv/config import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Docuseal functionality through MCP
6

Initialize Composio client

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Docuseal tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding
7

Create a Tool Router session

const session = await composio.create(
    userId as string,
    {
        toolkits: ['docuseal']
    }
);

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Docuseal tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
  • This approach allows the agent to dynamically load and use Docuseal tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "docuseal-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Docuseal MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Docuseal tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model
9

Set up interactive chat interface

let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Docuseal related question or task to the agent.\n");

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

rl.prompt();

rl.on('line', async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

    if (!trimmedInput) {
        rl.prompt();
        return;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
What's happening:
  • We initialize an empty conversationHistory list to maintain context across interactions
  • A readline interface is used to continuously accept user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the invoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully
10

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
What's happening:
  • We call the main() function to start the application

Complete Code

Here's the complete code to get you started with Docuseal and LangChain:

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['docuseal']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "docuseal-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Docuseal related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});

Conclusion

You've successfully built a LangChain agent that can interact with Docuseal through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.
TOOLS

Supported Tools

Every Docuseal action and event your agent gets out of the box.

Archive Submission

Tool to archive a submission by its unique identifier.

Archive Template

Tool to archive a specific template by its unique identifier.

Clone Template (v2)

Tool to clone an existing template into a new template with optional custom name, folder, and external_id.

Create Submission

Tool to create signature requests (submissions) from an existing document template and send them to submitters.

Create Submission From DOCX

Tool to create a one-off submission (signature request) from a DOCX document with dynamic content variables.

Create Submission From HTML

Tool to create a one-off submission request from HTML content with embedded field tags rendered as a fillable and signable form.

Create Submission From PDF

Tool to create a one-off submission (signature request) from a PDF file.

Create Submissions From Emails

Tool to create submissions for a document template and send them to specified email addresses.

Create Template from DOCX

Tool to create a fillable document template from a Microsoft Word DOCX file.

Create Template from HTML

Tool to create a fillable document template from HTML content with pre-defined fields.

Create Template From PDF

Tool to create a fillable document template from a PDF file.

Get Submission

Tool to retrieve detailed information about a specific submission.

Get Submission Documents

Tool to retrieve documents for a submission.

Get Submitter

Tool to retrieve detailed information about a submitter by ID.

Get Template

Tool to retrieve details of a specific template by its unique identifier.

List Submissions

List document submissions with filtering and cursor-based pagination.

List Submitters

Retrieve a paginated list of submitters with optional filtering.

List Templates (Enhanced)

Tool to retrieve a list of available document templates with pagination and filtering.

Merge Templates

Merge multiple DocuSeal templates into a single combined template.

Update Submitter

Tool to update submitter details, pre-fill or update field values, re-send signature request emails, or mark as auto-signed for automatic signing via API.

Update Template

Tool to update a document template by moving it to a different folder, changing its name, updating submitter roles, or unarchiving it.

Update Template Documents

Tool to add, remove, or replace documents in a template with provided PDF/DOCX file or HTML content.

FRAMEWORKS

How to build Docuseal MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Docuseal MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Docuseal MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Docuseal MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Docuseal MCP with Claude Cowork

Codex logo

Codex

Use Docuseal MCP with Codex

OpenClaw logo

OpenClaw

Use Docuseal MCP with OpenClaw

Hermes logo

Hermes

Use Docuseal MCP with Hermes

CLI logo

CLI

Use Docuseal MCP with CLI

Google ADK logo

Google ADK

Use Docuseal MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Docuseal MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Docuseal MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Docuseal MCP with LlamaIndex

CrewAI logo

CrewAI

Use Docuseal MCP with CrewAI

FAQ

Frequently asked questions

With a standalone Docuseal MCP server, the agents and LLMs can only access a fixed set of Docuseal tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Docuseal and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. LangChain fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Docuseal tools.

Yes, absolutely. You can configure which Docuseal scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Docuseal data and credentials are handled as safely as possible.

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A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

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As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

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Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

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