How to integrate Customgpt MCP with LangChain

This guide walks you through connecting Customgpt to LangChain using the Composio tool router. By the end, you'll have a working Customgpt agent that can list all your active customgpt projects, show chat history from your latest conversation, get usage limits for your account through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Customgpt account through Composio's Customgpt MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Introduction

This guide walks you through connecting Customgpt to LangChain using the Composio tool router. By the end, you'll have a working Customgpt agent that can list all your active customgpt projects, show chat history from your latest conversation, get usage limits for your account through natural language commands.

This guide will help you understand how to give your LangChain agent real control over a Customgpt account through Composio's Customgpt 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 Customgpt project to Composio
  • Create a Tool Router MCP session for Customgpt
  • Initialize an MCP client and retrieve Customgpt tools
  • Build a LangChain agent that can interact with Customgpt
  • 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 Customgpt MCP server, and what's possible with it?

The Customgpt MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your CustomGPT.ai account. It provides structured and secure access to your chatbot projects, so your agent can list, manage, update, and analyze your AI-powered chatbots and their licenses on your behalf.

  • Project and agent management: Effortlessly list all your CustomGPT projects, retrieve their details, and even delete agents you no longer need.
  • Comprehensive license handling: Let your agent fetch, update, or remove licenses attached to any of your chatbot projects, ensuring you always have the right access and compliance.
  • Chat conversation insights: Retrieve complete chat histories from your AI chatbot conversations to analyze user interactions or debug sessions.
  • User profile and usage monitoring: Automatically fetch your account profile and check on your usage limits, including agents, words, and queries, so you never exceed your quotas.
  • Project settings inspection: Quickly pull and review configuration details for any chatbot project to audit or adjust your bot's setup.

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 Customgpt 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 Customgpt 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: ['customgpt']
    }
);

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

Configure the agent with the MCP URL

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

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

Activate Persona Version

Restore a previous persona version for a CustomGPT agent.

Add Source to Project

Add a data source to a CustomGPT agent's knowledge base.

Clone CustomGPT Project

Tool to clone a CustomGPT agent (project).

Create Conversation

Tool to create a new conversation session for a CustomGPT agent.

Create CustomGPT Project

Tool to create a new CustomGPT agent from a sitemap URL or file upload.

Delete Page from Agent

Tool to delete a document from a CustomGPT agent's knowledge base.

Delete CustomGPT Project

Tool to delete a CustomGPT project by ID.

Delete CustomGPT Project License

Deletes a license from a CustomGPT project/agent.

Delete CustomGPT Source

Tool to delete a data source from a CustomGPT agent.

Export Leads

Export leads from a CustomGPT project.

Get Message

Tool to get message details from a CustomGPT conversation.

Get Message Trust Score

Tool to retrieve verification trust score for a message in a CustomGPT conversation.

Get Page Metadata

Tool to get document metadata including title, source URL, word count, and custom metadata fields.

Get Agent Plugins

Tool to retrieve plugin details for a specific CustomGPT agent (project).

Get CustomGPT Project

Tool to get agent details.

Get Project License

Tool to retrieve a license for a specific project.

Get Project Settings

Retrieve configuration settings for a specific CustomGPT agent/project.

Get Analytics Chart Data

Tool to retrieve analytics chart data for a CustomGPT project.

Get Conversation Analytics

Tool to get conversation analytics for a CustomGPT project.

Get Customer Intelligence Report

Tool to get customer intelligence for a CustomGPT project.

Get Traffic Analytics Report

Tool to retrieve traffic analytics for a CustomGPT agent/project.

Get Agent Statistics

Tool to get agent statistics.

Get Usage Limits

Get account usage limits showing current usage vs.

Get Current User Profile

Tool to retrieve the current user's profile information.

List Conversation Messages

Retrieves all messages from a CustomGPT conversation, including both user queries and AI responses.

List Agent Documents

Lists all documents in a CustomGPT agent's knowledge base.

List Persona Versions

Tool to list persona versions for a CustomGPT agent.

List CustomGPT Project Licenses

List all licenses for a CustomGPT project/agent.

List CustomGPT Projects

Lists all CustomGPT projects (agents) for the authenticated user.

List Agent Sources

Tool to list all data sources connected to an agent.

Reindex Page

Tool to reindex a document in CustomGPT knowledge base.

Search Team Members

Tool to search for team members by email address or user ID.

Submit Message Feedback

Tool to submit feedback (thumbs up/down) for a message in a CustomGPT conversation.

Update Page Metadata

Update document metadata for a specific page in a CustomGPT project.

Update Project

Updates an existing CustomGPT agent's name or configuration settings.

Update Project License

Updates the name of an existing license for a CustomGPT project/agent.

Update Project Settings

Update CustomGPT agent configuration settings.

Update Source Settings

Update source settings for a CustomGPT agent data source.

Update User Profile

Updates the authenticated user's profile information in CustomGPT.

Verify Message Accuracy

Tool to verify message accuracy by triggering a fact-checking verification process.

FRAMEWORKS

How to build Customgpt MCP Agent with another framework

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OpenAI Agents SDK

Use Customgpt MCP with OpenAI Agents SDK

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Claude Agent SDK

Use Customgpt MCP with Claude Agent SDK

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Claude Code

Use Customgpt MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Customgpt MCP with Claude Cowork

Codex logo

Codex

Use Customgpt MCP with Codex

OpenClaw logo

OpenClaw

Use Customgpt MCP with OpenClaw

Hermes logo

Hermes

Use Customgpt MCP with Hermes

CLI logo

CLI

Use Customgpt MCP with CLI

Google ADK logo

Google ADK

Use Customgpt MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Customgpt MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Customgpt MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Customgpt MCP with LlamaIndex

CrewAI logo

CrewAI

Use Customgpt MCP with CrewAI

FAQ

Frequently asked questions

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

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

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Co-founder, Slashy

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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Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

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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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Founder, Extra Thursday

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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Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

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