How to integrate Gmail MCP with LangChain

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Introduction

This guide walks you through connecting Gmail to LangChain using the Composio tool router. By the end, you'll have a working Gmail agent that can read emails, search your inbox, draft messages, manage labels, and organize threads through natural language commands.

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

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

TL;DR

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

The Gmail MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Gmail account. It provides structured and secure access to your email, so your agent can search, read, draft, organize, and even manage contacts in your mailbox—all on your behalf.

  • Advanced email search and retrieval: Effortlessly instruct your agent to fetch emails by sender, subject, label, date, or keywords, and even retrieve full message content or threads.
  • Automated drafting and sending: Have your agent create new email drafts, craft replies, add CC/BCC, include attachments, and handle threading to streamline communication.
  • Smart label and inbox organization: Let the agent create new labels, apply or remove labels from emails, and keep your inbox clutter-free by archiving or moving messages.
  • Contact and thread management: Fetch your Gmail contacts, pull entire conversation threads, or download specific attachments to make follow-ups a breeze.
  • Email and draft cleanup: Direct your agent to permanently delete emails or drafts, helping you maintain a tidy mailbox with minimal effort.

Supported Tools & Triggers

Tools
Triggers
Modify email labelsAdds and/or removes specified gmail labels for a message; ensure `message id` and all `label ids` are valid (use 'listlabels' for custom label ids).
Create email draftCreates a gmail email draft, supporting to/cc/bcc, subject, plain/html body (ensure `is html=true` for html), attachments, and threading.
Create labelCreates a new label with a unique name in the specified user's gmail account.
Delete DraftPermanently deletes a specific gmail draft using its id; ensure the draft exists and the user has necessary permissions for the given `user id`.
Delete messagePermanently deletes a specific email message by its id from a gmail mailbox; for `user id`, use 'me' for the authenticated user or an email address to which the authenticated user has delegated access.
Fetch emailsFetches a list of email messages from a gmail account, supporting filtering, pagination, and optional full content retrieval.
Fetch message by message IDFetches a specific email message by its id, provided the `message id` exists and is accessible to the authenticated `user id`.
Fetch Message by Thread IDRetrieves messages from a gmail thread using its `thread id`, where the thread must be accessible by the specified `user id`.
Get Gmail attachmentRetrieves a specific attachment by id from a message in a user's gmail mailbox, requiring valid message and attachment ids.
Get contactsFetches contacts (connections) for the authenticated google account, allowing selection of specific data fields and pagination.
Get PeopleRetrieves either a specific person's details (using `resource name`) or lists 'other contacts' (if `other contacts` is true), with `person fields` specifying the data to return.
Get ProfileRetrieves key gmail profile information (email address, message/thread totals, history id) for a user.
List draftsRetrieves a paginated list of email drafts from a user's gmail account.
List Gmail labelsRetrieves a list of all system and user-created labels for the specified gmail account.
List threadsRetrieves a list of email threads from a gmail account, identified by `user id` (email address or 'me'), supporting filtering and pagination.
Modify thread labelsAdds or removes specified existing label ids from a gmail thread, affecting all its messages; ensure the thread id is valid.
Move to TrashMoves an existing, non-deleted email message to the trash for the specified user.
Patch LabelPatches the specified label.
Remove labelPermanently deletes a specific, existing user-created gmail label by its id for a user; cannot delete system labels.
Reply to email threadSends a reply within a specific gmail thread using the original thread's subject, requiring a valid `thread id` and correctly formatted email addresses.
Search PeopleSearches contacts by matching the query against names, nicknames, emails, phone numbers, and organizations, optionally including 'other contacts'.
Send DraftSends the specified, existing draft to the recipients in the to, cc, and bcc headers.
Send EmailSends an email via gmail api using the authenticated user's google profile display name, requiring `is html=true` if the body contains html and valid `s3key`, `mimetype`, `name` for any attachment.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router 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 Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router 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 Gmail 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 Gmail tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

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

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

Configure the agent with the MCP URL

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

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "gmail-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 Gmail 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 Gmail 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 Gmail MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Gmail MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Gmail MCP with Claude Agent SDK

Google ADK

Google ADK

Use Gmail MCP with Google ADK

Vercel AI SDK

Vercel AI SDK

Use Gmail MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Gmail MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Gmail MCP with LlamaIndex

CrewAI

CrewAI

Use Gmail MCP with CrewAI

FAQ

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

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

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

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

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