How to integrate Google Chat MCP with LangChain

This guide walks you through connecting Google Chat to LangChain using the Composio tool router. By the end, you'll have a working Google Chat agent that can summarize recent messages in project space, send standup reminder to engineering space, list members of support chat space through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Google Chat account through Composio's Google Chat MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Introduction

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

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

Also integrate Google Chat with

OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenClaw Hermes CLI Google ADK Vercel AI SDK Mastra AI LlamaIndex CrewAI

TL;DR

Here's what you'll learn:

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

The Google Chat MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Google Chat account. It provides structured and secure access so your agent can perform Google Chat operations on your behalf.

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:

Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step10 STEPS

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

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

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

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 Google Chat functionality through MCP

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 Google Chat tools
Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

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

const url = session.mcp.url;

What's happening:

We're creating a Tool Router session that gives your agent access to Google Chat 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 Google Chat tools as needed

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "google_chat-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 Google Chat MCP server via HTTP
The client is configured with a name and the URL from our Tool Router session
getTools() retrieves all available Google Chat tools that the agent can use
We're creating a LangChain agent using the GPT-5 model

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 Google Chat 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

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 Google Chat 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: ['google_chat']
        }
    );

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

Complete Space Import

Completes the import process for an import-mode Google Chat space and makes it visible to users.

Create Custom Emoji

Creates a custom emoji in Google Chat for use within an organization.

Create Space Member

Creates a membership for a user, Chat app, or Google Group in a space.

Create Message

Creates a message in a Google Chat space.

Create Reaction

Creates an emoji reaction on a Google Chat message.

Create section

Creates a custom section in Google Chat for organizing conversations in the navigation panel.

Create Space

Creates a named space or group chat in Google Chat.

Delete Custom Emoji

Deletes a custom emoji from Google Chat.

Delete Member from Space

Removes a user, Google Group, or app from a space.

Delete Message

Deletes a message from a Google Chat space.

Delete Reaction

Deletes a reaction to a message.

Delete section

Deletes a custom section from Google Chat by its ID.

Delete space

Deletes a named space from Google Chat.

Download Media

Downloads the bytes of a Google Chat message attachment via the media API.

Find Direct Message

Returns the existing direct message space with the specified user.

Find Group Chats

Finds all group chat spaces that contain exactly the calling user and the specified users.

Get Attachment

Gets the metadata of a Google Chat message attachment.

Get Custom Emoji

Returns details about a custom emoji in Google Chat.

Get Chat Space Member

Returns details about a membership in a space.

Get Message

Returns details about a specific message in a Google Chat space.

Get Space

Returns details about a specific Google Chat space including configuration, membership count, and access settings.

Get Space Event

Returns an event from a Google Chat space.

Get Space Notification Setting

Gets the notification settings for a user in a specific space.

Get space read state

Returns details about a user's read state within a space.

Get thread read state

Returns details about a user's read state within a thread.

List custom emojis

Lists custom emojis visible to the authenticated user in Google Chat.

List Space Members

Lists memberships in a space.

List Messages

Lists messages in a space that the authenticated user is a member of.

List reactions on a message

Lists all reactions on a specific message in a Google Chat space.

List Section Items

Lists all items (such as spaces) within a specified section of a user's Google Chat.

List Sections

Lists all sections available to the authenticated user in Google Chat.

List Space Events

Lists events from a Google Chat space.

List Spaces

Lists spaces the authenticated user is a member of in Google Chat.

Move Section Item

Moves a space from one section to another in Google Chat.

Position Section in Sidebar

Changes the sort order of a section in the Google Chat sidebar.

Replace Message (Full)

Replaces an existing message in a Google Chat space using full replacement.

Search Spaces

Searches for spaces across a Google Workspace organization using administrator privileges.

Setup Space

Creates a space and adds specified users and groups to it.

Update Member

Updates a membership in a Google Chat space, such as changing a member's role between member and manager.

Update Message

Updates a message in a Google Chat space, modifying its text, cards, or other properties.

Update section

Updates a section's display name in Google Chat.

Update Space

Updates a Google Chat space's configuration including display name, description, guidelines, history settings, access settings, and permission settings.

Update Space Notification Setting

Updates the notification settings for a user in a space.

Update Space Read State

Updates a user's read state within a space, used to mark messages as read or unread.

Upload Media Attachment

Uploads a file as an attachment to a Google Chat space using the multipart media upload endpoint.

FRAMEWORKS

How to build Google Chat MCP Agent with another framework

OpenAI Agents SDK

Use Google Chat MCP with OpenAI Agents SDK

Claude Agent SDK

Use Google Chat MCP with Claude Agent SDK

Claude Code

Use Google Chat MCP with Claude Code

Claude Cowork

Use Google Chat MCP with Claude Cowork

Codex

Use Google Chat MCP with Codex

OpenClaw

Use Google Chat MCP with OpenClaw

Hermes

Use Google Chat MCP with Hermes

CLI

Use Google Chat MCP with CLI

Google ADK

Use Google Chat MCP with Google ADK

Vercel AI SDK

Use Google Chat MCP with Vercel AI SDK

Mastra AI

Use Google Chat MCP with Mastra AI

LlamaIndex

Use Google Chat MCP with LlamaIndex

CrewAI

Use Google Chat MCP with CrewAI

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

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Slack

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Slack is a channel-based messaging platform for teams and organizations. It helps people collaborate in real time, share files, and connect all their tools in one place.

Gong

BasicOauth2

Gong is a platform for video meetings, call recording, and team collaboration. It helps teams capture conversations, analyze calls, and turn insights into action.

FAQ

Frequently asked questions

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

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

Start with Google Chat.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Google Chat tool your agent needs.Free to start.

Start building

Customer stories

Teams ship real agents on Composio

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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati

Co-founder, Slashy

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.

Abhi Arya

Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave

CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu

Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola

Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche

Co-Founder, Ingram Technologies

How to integrate Google Chat MCP with LangChain

Connect Google Chat without auth hassles

Introduction

Also integrate Google Chat with

TL;DR

What is LangChain?

What is the Google Chat MCP server, and what's possible with it?

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

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import dependencies

Initialize Composio client

Create a Tool Router session

Configure the agent with the MCP URL

Set up interactive chat interface

Run the application

Complete Code

Conclusion

Supported Tools

How to build Google Chat MCP Agent with another framework

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

OpenClaw

Hermes

CLI

Google ADK

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

Explore Other Toolkits

Gmail

Outlook

Slack

Gong

Frequently asked questions

What are the differences in Tool Router MCP and Google Chat MCP?+

Can I use Tool Router MCP with LangChain?+

Can I manage the permissions and scopes for Google Chat while using Tool Router?+

How safe is my data with Composio Tool Router?+

Start with Google Chat.It takes 30 seconds.

Teams ship real agents on Composio