How to integrate Google Analytics MCP with LangChain

This guide walks you through connecting Google Analytics to LangChain using the Composio tool router. By the end, you'll have a working Google Analytics agent that can show all google analytics accounts i manage, get detailed info for a specific account, list audiences for your ga4 property through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Google Analytics account through Composio's Google Analytics MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Google Analytics tracks and reports website traffic, user behavior, and conversions. It helps marketers optimize performance and understand customer journeys.

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Introduction

This guide walks you through connecting Google Analytics to LangChain using the Composio tool router. By the end, you'll have a working Google Analytics agent that can show all google analytics accounts i manage, get detailed info for a specific account, list audiences for your ga4 property through natural language commands.

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

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

Also integrate Google Analytics with

ChatGPTOpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenCodeCursorVS CodeOpenClawHermesCLIGoogle ADKVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

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

The Google Analytics 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 Analytics account. It provides structured and secure access to your analytics data, enabling your agent to analyze traffic, retrieve account info, list audiences, and build custom datasets on your behalf.

  • View and manage analytics accounts: Let your agent retrieve detailed information about specific Google Analytics accounts or list all accounts you have access to.
  • Audience insights and segmentation: Easily have your agent list all audiences associated with a GA4 property, helping you understand and segment your visitors.
  • Create custom expanded datasets: Direct your agent to combine key dimensions and metrics into tailored datasets for deeper analysis and reporting.
  • Efficient property and resource discovery: Have your agent confirm the existence of properties and fetch their details, streamlining your analytics management workflow.

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 Google Analytics 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 Google Analytics 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: ['google_analytics']
    }
);

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

Configure the agent with the MCP URL

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

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

Archive Custom Dimension

Tool to archive a CustomDimension on a property.

Batch Run Pivot Reports

Tool to return multiple pivot reports in a batch for a GA4 property.

Batch Run Reports

Tool to return multiple analytics data reports in a batch.

Check Compatibility

Tool to list dimensions and metrics compatible with a GA4 report request.

Create Audience Export

Tool to create an audience export for Google Analytics.

Create Audience List

Tool to create an audience list for later retrieval by initiating a long-running asynchronous request.

Create Custom Dimension

Tool to create a CustomDimension for a Google Analytics property.

Create Custom Metric

Tool to create a custom metric in Google Analytics.

Create Expanded Data Set

Tool to create an expanded data set for a property.

Create Recurring Audience List

Tool to create a recurring audience list that automatically generates new audience lists daily based on the latest data.

Create Report Task

Tool to create a report task as a long-running asynchronous request for customized Google Analytics event data reports.

Create Rollup Property

Tool to create a roll-up property.

Get Account

Tool to retrieve a single Account by its resource name.

Get Attribution Settings

Tool to retrieve attribution configuration for a Google Analytics property.

Get Audience

Tool to retrieve a single Audience configuration from a Google Analytics property.

Get Audience Export

Tool to get configuration metadata about a specific audience export.

Get Audience List

Tool to get configuration metadata about a specific audience list.

Get Custom Dimension

Tool to retrieve a single CustomDimension by its resource name.

Get Data Retention Settings

Tool to retrieve data retention configuration for a Google Analytics property.

Get Data Sharing Settings

Tool to retrieve data sharing configuration for a Google Analytics account.

Get Google Signals Settings

Tool to retrieve Google Signals configuration settings for a GA4 property.

Get Key Event

Tool to retrieve a Key Event.

Get Metadata

Tool to get metadata for dimensions, metrics, and comparisons for a GA4 property.

Get Property

Tool to retrieve a single GA4 Property by its resource name.

Get Property Quotas Snapshot

Tool to retrieve all property quotas organized by category (corePropertyQuota, funnelPropertyQuota, realtimePropertyQuota) for a given GA4 property.

Get Recurring Audience List

Tool to get configuration metadata about a specific recurring audience list.

Get Report Task

Tool to get report metadata about a specific report task.

List Account Summaries

Tool to retrieve summaries of all Google Analytics accounts accessible by the caller.

List Accounts (v1beta)

Tool to list all Google Analytics accounts accessible by the caller using v1beta API.

List AdSense Links

Tool to list all AdSenseLinks on a property.

List Audience Exports

Tool to list all audience exports for a property.

List Audience Lists

Tool to list all audience lists for a specified property to help find and reuse existing lists.

List Audiences

Tool to list Audiences on a property.

List BigQuery Links

Tool to list BigQuery Links on a property.

List Calculated Metrics

List Calculated Metrics

List Channel Groups

Tool to list ChannelGroups on a property.

List Conversion Events

Tool to list conversion events on a property.

List Custom Dimensions

List Custom Dimensions

List Custom Metrics

Tool to list CustomMetrics on a property.

List DataStreams

Tool to list DataStreams on a property.

List Display & Video 360 Advertiser Links

Tool to list Display & Video 360 advertiser links on a property.

List DisplayVideo360 Advertiser Link Proposals

Tool to list DisplayVideo360AdvertiserLinkProposals on a property.

List Event Create Rules

Tool to list EventCreateRules configured on a web data stream.

List Expanded Data Sets

Tool to list ExpandedDataSets on a property.

List Firebase Links

Tool to list FirebaseLinks on a property.

List Google Ads Links

Tool to list GoogleAdsLinks on a property.

List Key Events

Tool to list Key Events.

List Measurement Protocol Secrets

Tool to list MeasurementProtocolSecrets under a data stream.

List Property

Tool to list GA4 properties based on filter criteria.

List Recurring Audience Lists

Tool to list all recurring audience lists for a GA4 property.

List Reporting Data Annotations

Tool to list all Reporting Data Annotations for a specific property.

List Report Tasks

Tool to list all report tasks for a Google Analytics property.

List Search Ads 360 Links

Tool to list all SearchAds360Links on a property.

List SKAdNetwork Conversion Value Schemas

Tool to list SKAdNetworkConversionValueSchema configurations for an iOS data stream.

List Subproperty Event Filters

Tool to list all subproperty event filters on a property.

List Subproperty Sync Configs

Tool to list SubpropertySyncConfig resources for managing subproperty synchronization configurations.

Provision Account Ticket

Tool to request a ticket for creating a Google Analytics account.

Query Audience Export

Tool to query a completed audience export.

Query Audience List

Tool to query an audience list.

Query Report Task

Tool to retrieve a report task's content.

Run Funnel Report

Tool to run a GA4 funnel report.

Run Pivot Report

Tool to run a customized pivot report of Google Analytics event data.

Run Realtime Report

Tool to run a customized realtime report of Google Analytics event data.

Run Report

Tool to run a customized GA4 data report.

Send Events

Tool to send event data to Google Analytics 4 using the Measurement Protocol.

Update Property

Tool to update an existing GA4 Property.

Validate Events

Tool to validate Measurement Protocol events before sending them to production.

FRAMEWORKS

How to build Google Analytics MCP Agent with another framework

ChatGPT logo

ChatGPT

Use Google Analytics MCP with ChatGPT

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Google Analytics MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Google Analytics MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Google Analytics MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Google Analytics MCP with Claude Cowork

Codex logo

Codex

Use Google Analytics MCP with Codex

Cursor logo

Cursor

Use Google Analytics MCP with Cursor

OpenClaw logo

OpenClaw

Use Google Analytics MCP with OpenClaw

Hermes logo

Hermes

Use Google Analytics MCP with Hermes

CLI logo

CLI

Use Google Analytics MCP with CLI

Google ADK logo

Google ADK

Use Google Analytics MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Google Analytics MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Google Analytics MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Google Analytics MCP with LlamaIndex

CrewAI logo

CrewAI

Use Google Analytics MCP with CrewAI

OpenCode logo

OpenCode

Use Google Analytics MCP with OpenCode

VS Code logo

VS Code

Use Google Analytics MCP with VS Code

FAQ

Frequently asked questions

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

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

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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.

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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.

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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.

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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.

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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.

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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.

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