How to integrate Gist MCP with LangChain

This guide walks you through connecting Gist to LangChain using the Composio tool router. By the end, you'll have a working Gist agent that can list all your public and private gists, show comments for gist with id abc123, check if i starred gist aa5a315d61ae9438b18d through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Gist account through Composio's Gist MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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GitHub Gist is a service for sharing code snippets and notes. It makes it easy to collaborate and organize your code or text, publicly or privately.

20 Tools

Introduction

This guide walks you through connecting Gist to LangChain using the Composio tool router. By the end, you'll have a working Gist agent that can list all your public and private gists, show comments for gist with id abc123, check if i starred gist aa5a315d61ae9438b18d through natural language commands.

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

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

Also integrate Gist 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 Gist project to Composio
  • Create a Tool Router MCP session for Gist
  • Initialize an MCP client and retrieve Gist tools
  • Build a LangChain agent that can interact with Gist
  • 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 Gist MCP server, and what's possible with it?

The Gist MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your GitHub Gist account. It provides structured and secure access to your gists, so your agent can create, manage, comment on, and organize code snippets and notes on your behalf.

  • Gist creation and management: Quickly ask your agent to create new public or private gists, update existing ones, or fetch details for any gist you own or have access to.
  • Commenting and collaboration: Let your agent add, list, retrieve, or delete comments on your gists to streamline discussion and feedback without manual effort.
  • Revision history and tracking: Effortlessly review a gist's revision history, retrieve specific past versions, and understand changes over time.
  • Star and fork management: Direct your agent to list your starred gists, check if you've starred a gist, or see all forks of a particular gist to keep track of popularity and collaboration.
  • Personalized gist organization: Have your agent list all your gists or your starred gists, making it easy to find, organize, and revisit important code snippets and notes.

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 Gist 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 Gist 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: ['gist']
    }
);

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

Configure the agent with the MCP URL

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

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

Check Gist Star

Check if the authenticated user has starred a specific gist.

Create Gist

Tool to create a new gist with one or more files.

Create Gist Comment

Tool to create a comment on a gist.

Delete Gist

Tool to delete a gist.

Delete Gist Comment

Tool to delete a comment on a gist.

Fork Gist

Tool to fork a gist.

Get Gist

Tool to retrieve a specific gist by its ID.

Get Gist Comment

Tool to get a specific comment on a gist.

Get Gist Revision

Tool to retrieve a specific gist revision.

List Gist Comments

Tool to list comments on a gist.

List Gist Commits

Tool to list the commit history of a gist.

List Gist Forks

Tool to list forks of a gist.

List Gists

Tool to list the authenticated user's gists or all public gists if called anonymously.

List Public Gists

Tool to list public gists sorted by most recently updated.

List Starred Gists

Tool to list the authenticated user's starred gists.

List User Gists

Tool to list public gists for a specified GitHub user.

Star a Gist

Star a GitHub gist.

Unstar a Gist

Unstar a GitHub gist.

Update Gist

Tool to update a gist's description and files.

Update Gist Comment

Tool to update a Gist comment.

FRAMEWORKS

How to build Gist MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Gist MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Gist MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Gist MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Gist MCP with Claude Cowork

Codex logo

Codex

Use Gist MCP with Codex

OpenClaw logo

OpenClaw

Use Gist MCP with OpenClaw

Hermes logo

Hermes

Use Gist MCP with Hermes

CLI logo

CLI

Use Gist MCP with CLI

Google ADK logo

Google ADK

Use Gist MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Gist MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Gist MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Gist MCP with LlamaIndex

CrewAI logo

CrewAI

Use Gist MCP with CrewAI

FAQ

Frequently asked questions

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

Yes, absolutely. You can configure which Gist 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 Gist 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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