How to integrate Customgpt MCP with LangChain

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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.

Also integrate Customgpt with

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.

Supported Tools & Triggers

Tools
Activate Persona VersionRestore a previous persona version for a CustomGPT agent.
Add Source to ProjectAdd a data source to a CustomGPT agent's knowledge base.
Clone CustomGPT ProjectTool to clone a CustomGPT agent (project).
Create ConversationTool to create a new conversation session for a CustomGPT agent.
Create CustomGPT ProjectTool to create a new CustomGPT agent from a sitemap URL or file upload.
Delete Page from AgentTool to delete a document from a CustomGPT agent's knowledge base.
Delete CustomGPT ProjectTool to delete a CustomGPT project by ID.
Delete CustomGPT Project LicenseDeletes a license from a CustomGPT project/agent.
Delete CustomGPT SourceTool to delete a data source from a CustomGPT agent.
Export LeadsExport leads from a CustomGPT project.
Get MessageTool to get message details from a CustomGPT conversation.
Get Message Trust ScoreTool to retrieve verification trust score for a message in a CustomGPT conversation.
Get Page MetadataTool to get document metadata including title, source URL, word count, and custom metadata fields.
Get Agent PluginsTool to retrieve plugin details for a specific CustomGPT agent (project).
Get CustomGPT ProjectTool to get agent details.
Get Project LicenseTool to retrieve a license for a specific project.
Get Project SettingsRetrieve configuration settings for a specific CustomGPT agent/project.
Get Analytics Chart DataTool to retrieve analytics chart data for a CustomGPT project.
Get Conversation AnalyticsTool to get conversation analytics for a CustomGPT project.
Get Customer Intelligence ReportTool to get customer intelligence for a CustomGPT project.
Get Traffic Analytics ReportTool to retrieve traffic analytics for a CustomGPT agent/project.
Get Agent StatisticsTool to get agent statistics.
Get Usage LimitsGet account usage limits showing current usage vs.
Get Current User ProfileTool to retrieve the current user's profile information.
List Conversation MessagesRetrieves all messages from a CustomGPT conversation, including both user queries and AI responses.
List Agent DocumentsLists all documents in a CustomGPT agent's knowledge base.
List Persona VersionsTool to list persona versions for a CustomGPT agent.
List CustomGPT Project LicensesList all licenses for a CustomGPT project/agent.
List CustomGPT ProjectsLists all CustomGPT projects (agents) for the authenticated user.
List Agent SourcesTool to list all data sources connected to an agent.
Reindex PageTool to reindex a document in CustomGPT knowledge base.
Search Team MembersTool to search for team members by email address or user ID.
Submit Message FeedbackTool to submit feedback (thumbs up/down) for a message in a CustomGPT conversation.
Update Page MetadataUpdate document metadata for a specific page in a CustomGPT project.
Update ProjectUpdates an existing CustomGPT agent's name or configuration settings.
Update Project LicenseUpdates the name of an existing license for a CustomGPT project/agent.
Update Project SettingsUpdate CustomGPT agent configuration settings.
Update Source SettingsUpdate source settings for a CustomGPT agent data source.
Update User ProfileUpdates the authenticated user's profile information in CustomGPT.
Verify Message AccuracyTool to verify message accuracy by triggering a fact-checking verification process.

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

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 Customgpt 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 Customgpt tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

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

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

Configure the agent with the MCP URL

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

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "customgpt-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 Customgpt 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 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.

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FAQ

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

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.

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 Customgpt tools.

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

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.

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 Customgpt data and credentials are handled as safely as possible.

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