How to integrate Ignisign MCP with LangChain

This guide walks you through connecting Ignisign to LangChain using the Composio tool router. By the end, you'll have a working Ignisign agent that can start a new signature request for a contract, add a new signer to this application, delete a completed document by its id through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Ignisign account through Composio's Ignisign MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Ignisign is an electronic signature platform for secure online document signing and management. Streamline agreements and digital paperwork with advanced workflow tools.

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Introduction

This guide walks you through connecting Ignisign to LangChain using the Composio tool router. By the end, you'll have a working Ignisign agent that can start a new signature request for a contract, add a new signer to this application, delete a completed document by its id through natural language commands.

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

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

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TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Ignisign project to Composio
  • Create a Tool Router MCP session for Ignisign
  • Initialize an MCP client and retrieve Ignisign tools
  • Build a LangChain agent that can interact with Ignisign
  • 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 Ignisign MCP server, and what's possible with it?

The Ignisign MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Ignisign account. It provides structured and secure access to your electronic signature workflows, so your agent can perform actions like sending signature requests, managing documents, onboarding signers, and handling signature operations on your behalf.

  • Automated signature request management: Let your agent create, cancel, or delete signature requests, streamlining the entire e-signature process from start to finish.
  • Document initialization and deletion: Have the agent initialize new documents for signing or permanently delete documents when they're no longer needed.
  • Signer onboarding and removal: Effortlessly add new signers to your application environment or remove existing ones as your workflows change.
  • Webhook endpoint management: Allow your agent to create or delete webhook endpoints, enabling real-time notifications and integrations for signature events.
  • Application context retrieval: Fetch global application settings and environment configurations so your agent always works with up-to-date information.

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 Ignisign 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 Ignisign 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: ['ignisign']
    }
);

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Ignisign 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 Ignisign tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "ignisign-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 Ignisign MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Ignisign 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 Ignisign 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 Ignisign 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: ['ignisign']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "ignisign-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 Ignisign 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 Ignisign 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 Ignisign action and event your agent gets out of the box.

Ignisign API Authentication

Tool to authenticate an application over Ignisign API and retrieve a JWT.

Cancel Signature Request

Cancel (close) a signature request to terminate it.

Initialize Document

Tool to initialize a document for a signature request.

Create Signer

Tool to create a new signer.

Create Webhook Endpoint

Tool to create a new webhook endpoint for an application.

Delete Document

Tool to delete a specific document by its ID.

Delete Ignisign Signature Request

Permanently deletes a signature request from Ignisign by its ID.

Delete Signer

Tool to revoke/delete a signer from an Ignisign application environment.

Delete Webhook Endpoint

Delete a webhook endpoint by its ID.

Get application context

Tool to retrieve the global context of an application.

Get Document Information

Tool to retrieve document metadata by ID.

Get Missing Signer Inputs

Tool to determine missing inputs needed for a signer in a specific signature profile.

Get Signature Request Details

Tool to retrieve detailed information for a specific signature request.

Get Signature Request Document

Tool to retrieve the document associated with a specific signature request.

Get Signature Requests

Retrieves a paginated list of signature requests for a specific Ignisign application and environment.

Get Signed Document

Tool to download the signed document (signature proof) for a signature request.

Get Signer Input Constraints

Tool to get signer input constraints.

Get Signer Inputs

Retrieves the inputs provided by a specific signer for a signature request.

Get Signer Profile

Retrieve detailed information about a specific signer profile by its ID.

Get Signer Profiles

Retrieve all signer profiles for a specific Ignisign application environment.

Get Webhooks

Retrieves all webhook endpoints configured for a specific Ignisign application environment.

Initialize Ignisign Signature Request

Initialize a new signature request in Ignisign.

List Documents

Tool to retrieve documents linked to a signature request.

Provide Document Content Data JSON

Provides JSON content to an existing document in Ignisign.

Provide Document Content File

Tool to provide file content for a document.

Provide Document Content Private File

Provides private document content by submitting its SHA-256 hash to IgniSign.

Publish Signature Request

Tool to publish a draft signature request.

Search Signers

Tool to search for signers within an application environment with pagination support.

Update Document Information

Tool to update document metadata.

Update Signature Request

Tool to partially update a signature request in DRAFT state.

Update Signer

Updates an existing signer's profile assignment.

Update Webhook Endpoint

Tool to update an existing webhook endpoint.

FRAMEWORKS

How to build Ignisign MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Ignisign MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Ignisign MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Ignisign MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Ignisign MCP with Claude Cowork

Codex logo

Codex

Use Ignisign MCP with Codex

OpenClaw logo

OpenClaw

Use Ignisign MCP with OpenClaw

Hermes logo

Hermes

Use Ignisign MCP with Hermes

CLI logo

CLI

Use Ignisign MCP with CLI

Google ADK logo

Google ADK

Use Ignisign MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Ignisign MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Ignisign MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Ignisign MCP with LlamaIndex

CrewAI logo

CrewAI

Use Ignisign MCP with CrewAI

FAQ

Frequently asked questions

With a standalone Ignisign MCP server, the agents and LLMs can only access a fixed set of Ignisign tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Ignisign 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 Ignisign tools.

Yes, absolutely. You can configure which Ignisign 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 Ignisign data and credentials are handled as safely as possible.

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