# How to integrate Gist MCP with LangChain

```json
{
  "title": "How to integrate Gist MCP with LangChain",
  "toolkit": "Gist",
  "toolkit_slug": "gist",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/gist/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/gist/framework/langchain.md",
  "updated_at": "2026-05-12T10:13:01.353Z"
}
```

## 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 SDK](https://composio.dev/toolkits/gist/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/gist/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/gist/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/gist/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/gist/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/gist/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/gist/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/gist/framework/cli)
- [Google ADK](https://composio.dev/toolkits/gist/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/gist/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/gist/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/gist/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/gist/framework/crew-ai)

## 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.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `GIST_CHECK_GIST_STAR` | Check Gist Star | Check if the authenticated user has starred a specific gist. Returns True if the gist is starred, False if not starred or if the gist doesn't exist. This is a read-only, idempotent operation that requires authentication but no special permissions. |
| `GIST_CREATE_GIST` | Create Gist | Tool to create a new gist with one or more files. Use when you need to create a code snippet or text file to share. Note: Do not name your files 'gistfile' with a numerical suffix. |
| `GIST_CREATE_GIST_COMMENT` | Create Gist Comment | Tool to create a comment on a gist. Use when you need to add a comment to an existing gist. |
| `GIST_DELETE_GIST` | Delete Gist | Tool to delete a gist. Use when you have a gist_id and want to permanently remove that gist. Example prompt: "Delete gist 'aa5a315d61ae9438b18d'". |
| `GIST_DELETE_GIST_COMMENT` | Delete Gist Comment | Tool to delete a comment on a gist. Use when you have both the gist_id and comment_id and want to remove that comment. Example prompt: "Delete comment 42 from gist 'aa5a315d61ae9438b18d'". |
| `GIST_FORK_GIST` | Fork Gist | Tool to fork a gist. Use when you need to create a copy of an existing gist under your own account. |
| `GIST_GET_GIST` | Get Gist | Tool to retrieve a specific gist by its ID. Use when you have a gist_id and need complete gist details. |
| `GIST_GET_GIST_COMMENT` | Get Gist Comment | Tool to get a specific comment on a gist. Use when you need to retrieve details of a particular comment given gist_id and comment_id. |
| `GIST_GET_GIST_REVISION` | Get Gist Revision | Tool to retrieve a specific gist revision. Use when you need details of a past state for an existing gist by commit SHA. |
| `GIST_LIST_GIST_COMMENTS` | List Gist Comments | Tool to list comments on a gist. Use after confirming the gist_id to retrieve comments for a specific gist. Example: 'List comments for gist abc123'. |
| `GIST_LIST_GIST_COMMITS` | List Gist Commits | Tool to list the commit history of a gist. Use after you have the gist ID to review its revisions. |
| `GIST_LIST_GIST_FORKS` | List Gist Forks | Tool to list forks of a gist. Use after obtaining a gist_id to retrieve all forks for the gist. |
| `GIST_LIST_GISTS` | List Gists | Tool to list the authenticated user's gists or all public gists if called anonymously. Use after setting a valid GitHub token in headers. |
| `GIST_LIST_PUBLIC_GISTS` | List Public Gists | Tool to list public gists sorted by most recently updated. Use when you need to discover recent public gists. Note: with pagination, you can fetch up to 3000 gists. |
| `GIST_LIST_STARRED_GISTS` | List Starred Gists | Tool to list the authenticated user's starred gists. Use when you need to retrieve all gists the user has starred. |
| `GIST_LIST_USER_GISTS` | List User Gists | Tool to list public gists for a specified GitHub user. Use when you have a username and need their gists. |
| `GIST_STAR_GIST` | Star a Gist | Star a GitHub gist. This operation is idempotent and will succeed even if the gist is already starred. |
| `GIST_UNSTAR_GIST` | Unstar a Gist | Unstar a GitHub gist. This operation is idempotent and will succeed even if the gist is not currently starred. |
| `GIST_UPDATE_GIST` | Update Gist | Tool to update a gist's description and files. Use when you need to modify gist content, rename files, or delete files from a gist. |
| `GIST_UPDATE_GIST_COMMENT` | Update Gist Comment | Tool to update a Gist comment. Updates an existing comment on a gist. You must be the author of the comment to update it. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Gist MCP server is an implementation of the Model Context Protocol that connects your AI agent to Gist. It provides structured and secure access so your agent can perform Gist operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

No description provided.

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

No description provided.
```python
pip install composio-langchain langchain-mcp-adapters langchain python-dotenv
```

```typescript
npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv
```

### 3. Set up environment variables

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
```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
```

### 4. Import dependencies

No description provided.
```python
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()
```

```typescript
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();
```

### 5. Initialize Composio client

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
```python
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")
```

```typescript
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()
    });
```

### 6. Create a Tool Router session

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
```python
# Create Tool Router session for Gist
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['gist']
)

url = session.mcp.url
```

```typescript
const session = await composio.create(
    userId as string,
    {
        toolkits: ['gist']
    }
);

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "gist-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)
```

```typescript
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 });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Gist 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")
```

```typescript
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);
    });
```

### 9. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Complete Code

```python
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=['gist']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "gist-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 Gist 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())
```

```typescript
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.

## How to build Gist MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/gist/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/gist/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/gist/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/gist/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/gist/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/gist/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/gist/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/gist/framework/cli)
- [Google ADK](https://composio.dev/toolkits/gist/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/gist/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/gist/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/gist/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/gist/framework/crew-ai)

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- [Apiverve](https://composio.dev/toolkits/apiverve) - Apiverve delivers a suite of powerful APIs that simplify integration for developers. It's designed for reliability and scalability so you can build faster, smarter applications without the integration headache.
- [Appcircle](https://composio.dev/toolkits/appcircle) - Appcircle is an enterprise-grade mobile CI/CD platform for building, testing, and publishing mobile apps. It streamlines mobile DevOps so teams ship faster and with more confidence.
- [Appdrag](https://composio.dev/toolkits/appdrag) - Appdrag is a cloud platform for building websites, APIs, and databases with drag-and-drop tools and code editing. It accelerates development and iteration by combining hosting, database management, and low-code features in one place.
- [Appveyor](https://composio.dev/toolkits/appveyor) - AppVeyor is a cloud-based continuous integration service for building, testing, and deploying applications. It helps developers automate and streamline their software delivery pipelines.
- [Backendless](https://composio.dev/toolkits/backendless) - Backendless is a backend-as-a-service platform for mobile and web apps, offering database, file storage, user authentication, and APIs. It helps developers ship scalable applications faster without managing server infrastructure.
- [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code.
- [Bench](https://composio.dev/toolkits/bench) - Bench is a benchmarking tool for automated performance measurement and analysis. It helps you quickly evaluate, compare, and track your systems or workflows.
- [Better stack](https://composio.dev/toolkits/better_stack) - Better Stack is a monitoring, logging, and incident management solution for apps and services. It helps teams ensure application reliability and performance with real-time insights.
- [Bitbucket](https://composio.dev/toolkits/bitbucket) - Bitbucket is a Git-based code hosting and collaboration platform for teams. It enables secure repository management and streamlined code reviews.
- [Blazemeter](https://composio.dev/toolkits/blazemeter) - Blazemeter is a continuous testing platform for web and mobile app performance. It empowers teams to automate and analyze large-scale tests with ease.
- [Blocknative](https://composio.dev/toolkits/blocknative) - Blocknative delivers real-time mempool monitoring and transaction management for public blockchains. Instantly track pending transactions and optimize blockchain interactions with live data.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Gist MCP?

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.

### 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 Gist tools.

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

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.

### 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 Gist data and credentials are handled as safely as possible.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)