How to integrate Google Analytics MCP with LangChain

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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.

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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.

Supported Tools & Triggers

Tools
Archive Custom DimensionTool to archive a CustomDimension on a property.
Batch Run Pivot ReportsTool to return multiple pivot reports in a batch for a GA4 property.
Batch Run ReportsTool to return multiple analytics data reports in a batch.
Check CompatibilityTool to list dimensions and metrics compatible with a GA4 report request.
Create Audience ExportTool to create an audience export for Google Analytics.
Create Audience ListTool to create an audience list for later retrieval by initiating a long-running asynchronous request.
Create Custom DimensionTool to create a CustomDimension for a Google Analytics property.
Create Custom MetricTool to create a custom metric in Google Analytics.
Create Expanded Data SetTool to create an expanded data set for a property.
Create Recurring Audience ListTool to create a recurring audience list that automatically generates new audience lists daily based on the latest data.
Create Report TaskTool to create a report task as a long-running asynchronous request for customized Google Analytics event data reports.
Create Rollup PropertyTool to create a roll-up property.
Get AccountTool to retrieve a single Account by its resource name.
Get Attribution SettingsTool to retrieve attribution configuration for a Google Analytics property.
Get AudienceTool to retrieve a single Audience configuration from a Google Analytics property.
Get Audience ExportTool to get configuration metadata about a specific audience export.
Get Audience ListTool to get configuration metadata about a specific audience list.
Get Custom DimensionTool to retrieve a single CustomDimension by its resource name.
Get Data Retention SettingsTool to retrieve data retention configuration for a Google Analytics property.
Get Data Sharing SettingsTool to retrieve data sharing configuration for a Google Analytics account.
Get Google Signals SettingsTool to retrieve Google Signals configuration settings for a GA4 property.
Get Key EventTool to retrieve a Key Event.
Get MetadataTool to get metadata for dimensions, metrics, and comparisons for a GA4 property.
Get PropertyTool to retrieve a single GA4 Property by its resource name.
Get Property Quotas SnapshotTool to retrieve all property quotas organized by category (corePropertyQuota, funnelPropertyQuota, realtimePropertyQuota) for a given GA4 property.
Get Recurring Audience ListTool to get configuration metadata about a specific recurring audience list.
Get Report TaskTool to get report metadata about a specific report task.
List Account SummariesTool 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 LinksTool to list all AdSenseLinks on a property.
List Audience ExportsTool to list all audience exports for a property.
List Audience ListsTool to list all audience lists for a specified property to help find and reuse existing lists.
List AudiencesTool to list Audiences on a property.
List BigQuery LinksTool to list BigQuery Links on a property.
List Calculated MetricsList Calculated Metrics
List Channel GroupsTool to list ChannelGroups on a property.
List Conversion EventsTool to list conversion events on a property.
List Custom DimensionsList Custom Dimensions
List Custom MetricsTool to list CustomMetrics on a property.
List DataStreamsTool to list DataStreams on a property.
List Display & Video 360 Advertiser LinksTool to list Display & Video 360 advertiser links on a property.
List DisplayVideo360 Advertiser Link ProposalsTool to list DisplayVideo360AdvertiserLinkProposals on a property.
List Event Create RulesTool to list EventCreateRules configured on a web data stream.
List Expanded Data SetsTool to list ExpandedDataSets on a property.
List Firebase LinksTool to list FirebaseLinks on a property.
List Google Ads LinksTool to list GoogleAdsLinks on a property.
List Key EventsTool to list Key Events.
List Measurement Protocol SecretsTool to list MeasurementProtocolSecrets under a data stream.
List PropertyTool to list GA4 properties based on filter criteria.
List Recurring Audience ListsTool to list all recurring audience lists for a GA4 property.
List Reporting Data AnnotationsTool to list all Reporting Data Annotations for a specific property.
List Report TasksTool to list all report tasks for a Google Analytics property.
List Search Ads 360 LinksTool to list all SearchAds360Links on a property.
List SKAdNetwork Conversion Value SchemasTool to list SKAdNetworkConversionValueSchema configurations for an iOS data stream.
List Subproperty Event FiltersTool to list all subproperty event filters on a property.
List Subproperty Sync ConfigsTool to list SubpropertySyncConfig resources for managing subproperty synchronization configurations.
Provision Account TicketTool to request a ticket for creating a Google Analytics account.
Query Audience ExportTool to query a completed audience export.
Query Audience ListTool to query an audience list.
Query Report TaskTool to retrieve a report task's content.
Run Funnel ReportTool to run a GA4 funnel report.
Run Pivot ReportTool to run a customized pivot report of Google Analytics event data.
Run Realtime ReportTool to run a customized realtime report of Google Analytics event data.
Run ReportTool to run a customized GA4 data report.
Send EventsTool to send event data to Google Analytics 4 using the Measurement Protocol.
Update PropertyTool to update an existing GA4 Property.
Validate EventsTool to validate Measurement Protocol events before sending them to production.

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

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 Google Analytics 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 Google Analytics tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

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

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

Configure the agent with the MCP URL

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

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "google_analytics-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 Google Analytics 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 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.

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FAQ

What are the differences in Tool Router MCP and Google Analytics MCP?

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.

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 Google Analytics tools.

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

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.

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 Google Analytics data and credentials are handled as safely as possible.

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