# How to integrate Gamma MCP with LangChain

```json
{
  "title": "How to integrate Gamma MCP with LangChain",
  "toolkit": "Gamma",
  "toolkit_slug": "gamma",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/gamma/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/gamma/framework/langchain.md",
  "updated_at": "2026-05-12T10:12:31.273Z"
}
```

## Introduction

This guide walks you through connecting Gamma to LangChain using the Composio tool router. By the end, you'll have a working Gamma agent that can create a pitch deck for a startup idea, generate an interactive onboarding presentation, summarize a research paper as slides through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Gamma account through Composio's Gamma MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Gamma with

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

## TL;DR

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

The Gamma MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Gamma account. It provides structured and secure access to Gamma’s AI-powered content creation platform, so your agent can generate new presentations, monitor generation progress, and retrieve finished files on your behalf.
- AI-driven presentation generation: Instantly create beautiful, interactive decks or documents through simple prompts, letting your agent handle the heavy lifting.
- Automated content creation: Ask your agent to produce engaging summaries, reports, or educational material as shareable Gamma presentations.
- Real-time generation status tracking: Have your agent monitor the progress of each presentation request and keep you updated on completion status.
- Direct retrieval of generated files: Let your agent fetch download URLs for finished Gamma files, making it easy to share or embed them anywhere.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `GAMMA_CREATE_FROM_TEMPLATE` | Create from Template | Tool to create new Gamma content based on an existing template. Use when you need to generate content with a predefined structure/layout by providing custom instructions and prompt. The API creates content asynchronously. This action polls the generation status and returns the gammaUrl when complete, or a generationId if the 2-minute timeout is reached. |
| `GAMMA_GENERATE_GAMMA` | Generate a Gamma | Generate a Gamma presentation, document, webpage, or social media content using AI. Documentation: https://developers.gamma.app/docs/generate-api-parameters-explained The API creates content asynchronously. Poll the returned generationId to check status. |
| `GAMMA_GET_GAMMA_FILE_URLS` | Get Gamma File URLs | Retrieve generation status and file URLs. Poll this endpoint every ~5 seconds until status is 'completed'. Docs: https://developers.gamma.app/reference/get-generation-status |
| `GAMMA_LIST_FOLDERS` | List Folders | Tool to retrieve a paginated list of folders in your Gamma workspace. Use when you need folder IDs to organize generated content or to search for specific folders by name. |
| `GAMMA_LIST_THEMES` | List Themes | Fetch the list of themes available in your workspace. Returns both standard (global) and custom (workspace-specific) themes in a paginated format. Use this to discover available theme IDs and names for use with the Generate API. Filter by name using the query parameter. |

## Supported Triggers

None listed.

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

The Gamma MCP server is an implementation of the Model Context Protocol that connects your AI agent to Gamma. It provides structured and secure access so your agent can perform Gamma 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 Gamma 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 Gamma 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 Gamma tools as needed
```python
# Create Tool Router session for Gamma
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['gamma']
)

url = session.mcp.url
```

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

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

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

No description provided.
```python
client = MultiServerMCPClient({
    "gamma-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({
    "gamma-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 Gamma 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 Gamma 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=['gamma']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "gamma-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 Gamma 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: ['gamma']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "gamma-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 Gamma 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 Gamma 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 Gamma MCP Agent with another framework

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

## Related Toolkits

- [Figma](https://composio.dev/toolkits/figma) - Figma is a collaborative interface design tool for teams and individuals. It streamlines design workflows with real-time collaboration and easy sharing.
- [Abyssale](https://composio.dev/toolkits/abyssale) - Abyssale is a creative automation platform for generating images, videos, GIFs, PDFs, and HTML5 content programmatically. It streamlines and scales visual content production for marketing, design, and operations teams.
- [Alttext ai](https://composio.dev/toolkits/alttext_ai) - AltText.ai is a service that generates alt text for images automatically. It helps boost accessibility and SEO for your visual content.
- [Bannerbear](https://composio.dev/toolkits/bannerbear) - Bannerbear is an API-driven platform for generating images and videos automatically at scale. It helps businesses create custom graphics, social visuals, and marketing assets using powerful templates.
- [Canva](https://composio.dev/toolkits/canva) - Canva is a drag-and-drop design suite for creating professional graphics, presentations, and marketing materials. It makes it easy for anyone to design with beautiful templates and a vast library of elements.
- [Claid ai](https://composio.dev/toolkits/claid_ai) - Claid.ai delivers AI-driven image editing APIs for tasks like background removal, upscaling, and color correction. It helps automate and enhance image workflows with powerful, developer-friendly tools.
- [Cloudinary](https://composio.dev/toolkits/cloudinary) - Cloudinary is a cloud-based platform for managing, uploading, and transforming images and videos. It streamlines media workflows and delivers optimized assets globally.
- [Cults](https://composio.dev/toolkits/cults) - Cults is a digital marketplace for 3D printing models, connecting designers and makers. It lets creators share, sell, and discover a huge variety of printable designs easily.
- [DeepImage](https://composio.dev/toolkits/deepimage) - DeepImage is an AI-powered image enhancer and upscaler. Get higher-quality images with just a few clicks.
- [Dreamstudio](https://composio.dev/toolkits/dreamstudio) - DreamStudio is Stability AI’s platform for generating and editing images with AI. It lets you easily turn ideas into stunning visuals, fast.
- [Dynapictures](https://composio.dev/toolkits/dynapictures) - Dynapictures is a cloud-based platform for generating personalized images at scale. Instantly create hundreds of custom visuals using your data sources, like Google Sheets.
- [Fal.ai](https://composio.dev/toolkits/fal_ai) - Fal.ai is a generative media platform offering 600+ AI models for images, video, voice, and audio. Developers use Fal.ai for fast, scalable access to cutting-edge generative AI tools.
- [Html to image](https://composio.dev/toolkits/html_to_image) - Html to image converts HTML and CSS into images or captures web page screenshots. Instantly generate visuals from code or web content—no manual screenshots needed.
- [Imagior](https://composio.dev/toolkits/imagior) - Imagior is an AI-powered image generation platform that lets you create and customize images using dynamic templates and APIs. Perfect for businesses and creators needing fast, scalable visuals without design hassle.
- [Imejis io](https://composio.dev/toolkits/imejis_io) - Imejis io is an API-based image generation platform with powerful customization and template support. It lets you create and modify images in seconds, no manual design work required.
- [Imgix](https://composio.dev/toolkits/imgix) - Imgix is a real-time image processing and delivery service for developers. It helps you optimize, transform, and deliver images efficiently at any scale.
- [Kraken io](https://composio.dev/toolkits/kraken_io) - Kraken.io is an image optimization and compression platform. It helps you shrink image file sizes while keeping visual quality intact.
- [Logo dev](https://composio.dev/toolkits/logo_dev) - Logo.dev is an API and database for high-resolution company logos and brand metadata. Instantly fetch official logos from any domain without scraping or manual searching.
- [Miro](https://composio.dev/toolkits/miro) - Miro is a collaborative online whiteboard platform for teams to brainstorm, design, and manage projects visually. It streamlines teamwork by enabling real-time idea sharing, diagramming, and workflow planning in a single space.
- [Mural](https://composio.dev/toolkits/mural) - Mural is a digital whiteboard platform for distributed visual collaboration. It helps teams brainstorm, map ideas, and diagram together in real time.

## Frequently Asked Questions

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

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

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

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

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