How to integrate Docuseal MCP with LangChain

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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 my account, create a new template from html content, start a signature workflow from a pdf file, merge multiple templates into a single document 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.

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.

Supported Tools & Triggers

Tools
Archive TemplateTool to archive a specific template by its unique identifier.
Clone TemplateTool to clone an existing template by its id with a new name.
Create Submission From PDFTool to create a one-off submission from a pdf file.
Create Template from HTMLTool to create a template from html content.
Get TemplateTool to retrieve details of a specific template by its unique identifier.
List SubmissionsTool to list all document submissions with optional pagination and document filtering.
List SubmittersTool to retrieve a list of all submitters.
List TemplatesTool to retrieve a list of all templates.
Merge TemplatesTool to merge multiple templates into one with a new name.
Update TemplateTool to update details of a specific template, including name and folder.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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

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

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.

Install dependencies

pip install composio-langchain langchain-mcp-adapters langchain python-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 is the core agent framework
  • python-dotenv loads environment variables

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

Import dependencies

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

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

Initialize Composio client

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
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

Create a Tool Router session

# Create Tool Router session for Docuseal
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['docuseal']
)

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

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "docuseal-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("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
  • get_tools() retrieves all available Docuseal tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

conversation_history = []

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

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts 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 ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

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

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['docuseal']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "docuseal-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Docuseal related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())

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.

How to build Docuseal MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Docuseal MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Docuseal MCP with Claude Agent SDK

Google ADK

Google ADK

Use Docuseal MCP with Google ADK

Vercel AI SDK

Vercel AI SDK

Use Docuseal MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Docuseal MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Docuseal MCP with LlamaIndex

CrewAI

CrewAI

Use Docuseal MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Docuseal MCP?

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.

Can I use Tool Router MCP with LangChain?

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.

Can I manage the permissions and scopes for Docuseal while using Tool Router?

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.

How safe is my data with Composio Tool Router?

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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