How to integrate Googlecontacts MCP with LangChain

This guide walks you through connecting Googlecontacts to LangChain using the Composio tool router. By the end, you'll have a working Googlecontacts agent that can find contacts at acme corporation, create contact for new sales lead, update phone number for priya shah through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Googlecontacts account through Composio's Googlecontacts MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Googlecontacts is Google’s contact management service powered by the Google People API. It keeps names, emails, phone numbers, and contact details synced across Google Workspace.

24 Tools

Introduction

This guide walks you through connecting Googlecontacts to LangChain using the Composio tool router. By the end, you'll have a working Googlecontacts agent that can find contacts at acme corporation, create contact for new sales lead, update phone number for priya shah through natural language commands.

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

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

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

The Googlecontacts MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Googlecontacts account. It provides structured and secure access to your contacts, contact groups, other contacts, and domain directory, so your agent can search, create, update, delete, and organize contacts on your behalf.

  • Contact search and lookup: Instruct your agent to search your contacts, retrieve individual people, or list all saved connections.
  • Contact creation and updates: Have your agent create new contacts, update existing details, or add many contacts at once.
  • Contact groups and membership: Let the agent create, rename, list, or delete contact groups and manage which contacts belong to them.
  • Directory and other contact discovery: Direct your agent to search your organization’s directory, review other contacts, and copy useful people into your main contacts.
  • Contact cleanup and photos: Have your agent delete individual contacts or batches of contacts, then add, replace, or remove contact photos.

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 Googlecontacts 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 Googlecontacts 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: ['googlecontacts']
    }
);

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

Configure the agent with the MCP URL

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

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

Batch create contacts

Create a batch of new contacts in Google Contacts.

Batch get contact groups

Get a list of contact groups owned by the authenticated user by specifying a list of contact group resource names.

Batch Update Google Contacts

Update a batch of contacts in Google Contacts and return the updated contact data.

Copy Other Contact to My Contacts

Copies an Other contact to a new contact in the user's myContacts group.

Create Contact

Create a new contact in Google Contacts and return the person resource for that contact.

Create Contact Group

Create a new contact group owned by the authenticated user.

Delete Google Contact

Delete a contact person from Google Contacts.

Delete contact group

Deletes an existing contact group owned by the authenticated user by specifying the contact group resource name.

Delete Contact Photo

Delete a contact's photo from Google Contacts.

Batch Delete Google Contacts

Delete a batch of contacts from Google Contacts.

Batch get people

Batch retrieves information about multiple people from Google Contacts.

Get Contact Group

Retrieves a specific contact group owned by the authenticated user by specifying the contact group resource name.

Get Person

Provides information about a person by specifying a resource name.

List Connections

Lists the connections (contacts) for the authenticated user.

List Contact Groups

List all contact groups owned by the authenticated user.

List Directory People

Lists domain profiles and domain contacts in the authenticated user's domain directory.

List Other Contacts

Lists "Other contacts" from Google People API.

Modify Contact Group Members

Modifies the members of a contact group by adding or removing contact resource names.

Search Contacts

Searches the authenticated user's contacts for matches against the provided query.

Search Domain Directory People

Search domain directory people in Google Contacts.

Search Other Contacts

Searches other contacts from Google People API that match a query string.

Update Google Contact

Update contact data for an existing contact person.

Update Contact Group

Update the name of an existing contact group owned by the authenticated user.

Update Contact Photo

Update a contact's photo.

FRAMEWORKS

How to build Googlecontacts MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Googlecontacts MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Googlecontacts MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Googlecontacts MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Googlecontacts MCP with Claude Cowork

Codex logo

Codex

Use Googlecontacts MCP with Codex

OpenClaw logo

OpenClaw

Use Googlecontacts MCP with OpenClaw

Hermes logo

Hermes

Use Googlecontacts MCP with Hermes

CLI logo

CLI

Use Googlecontacts MCP with CLI

Google ADK logo

Google ADK

Use Googlecontacts MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Googlecontacts MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Googlecontacts MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Googlecontacts MCP with LlamaIndex

CrewAI logo

CrewAI

Use Googlecontacts MCP with CrewAI

FAQ

Frequently asked questions

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

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

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