How to integrate Google Analytics MCP with LlamaIndex

This guide walks you through connecting Google Analytics to LlamaIndex 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 LlamaIndex 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 LlamaIndex 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 LlamaIndex 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

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TL;DR

Here's what you'll learn:
  • Set your OpenAI and Composio API keys
  • Install LlamaIndex and Composio packages
  • Create a Composio Tool Router session for Google Analytics
  • Connect LlamaIndex to the Google Analytics MCP server
  • Build a Google Analytics-powered agent using LlamaIndex
  • Interact with Google Analytics through natural language

What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.

Key features include:

  • ReAct Agent: Reasoning and acting pattern for tool-using agents
  • MCP Tools: Native support for Model Context Protocol
  • Context Management: Maintain conversation context across interactions
  • Async Support: Built for async/await patterns

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 you begin, make sure you have:
  • Python 3.8/Node 16 or higher installed
  • A Composio account with the API key
  • An OpenAI API key
  • A Google Analytics account and project
  • Basic familiarity with async Python/Typescript
2

Getting API Keys for OpenAI, Composio, and Google Analytics

OpenAI API key (OPENAI_API_KEY)
  • Go to the OpenAI dashboard
  • Create an API key if you don't have one
  • Assign it to OPENAI_API_KEY in .env
Composio API key and user ID
  • Log into the Composio dashboard
  • Copy your API key from Settings
    • Use this as COMPOSIO_API_KEY
  • Pick a stable user identifier (email or ID)
    • Use this as COMPOSIO_USER_ID
3

Installing dependencies

npm install @composio/llamaindex @llamaindex/openai @llamaindex/tools @llamaindex/workflow dotenv

Create a new Typescript project and install the necessary dependencies:

  • @composio/llamaindex: Composio's LlamaIndex integration
  • @llamaindex/openai: OpenAI LLM integration
  • @llamaindex/tools: MCP client for LlamaIndex
  • @llamaindex/workflow: Workflow framework for LlamaIndex
  • dotenv: Environment variable management
4

Set environment variables

bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id

Create a .env file in your project root:

These credentials will be used to:

  • Authenticate with OpenAI's GPT-5 model
  • Connect to Composio's Tool Router
  • Identify your Composio user session for Google Analytics access
5

Import modules

import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

Create a new file called google analytics_llamaindex_agent.ts and import the required modules:

Key imports:

  • dotenv.config loads .env at runtime
  • readline gives us a simple CLI chat loop
  • Composio is the main Composio SDK client
  • mcp connects to an MCP endpoint
  • createAgent builds a LlamaIndex agent
  • openai configures the LLM backend
6

Load environment variables and initialize Composio

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!COMPOSIO_API_KEY) throw new Error("COMPOSIO_API_KEY is not set");
if (!COMPOSIO_USER_ID) throw new Error("COMPOSIO_USER_ID is not set");

What's happening:

This ensures missing credentials cause early, clear errors before the agent attempts to initialise.

7

Create a Tool Router session and build the agent function

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["google_analytics"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
        description : "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Google Analytics actions." ,
    llm,
    tools,
  });

  return agent;
}

What's happening here:

  • We create a Composio client using your API key and configure it with the LlamaIndex provider
  • We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, google analytics)
  • The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
  • LlamaIndex will connect to this endpoint to dynamically discover and use the available Google Analytics tools.
  • The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.
8

Create an interactive chat loop

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

What's happening:

  • We're creating a direct terminal interface to chat with Google Analytics
  • The LLM's responses are streamed to the CLI for faster interaction.
  • The agent uses context to maintain conversation history
  • The agent processes the request, selects appropriate Google Analytics tools, and returns a result
  • We extract the answer from the result data structure and display it to the user
  • You can type 'quit' or 'exit' to stop the chat loop gracefully
  • Agent responses and any errors are streamed in a clear, readable format
9

Define the main entry point

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err) {
    console.error("Failed to start agent:", err);
    process.exit(1);
  }
}

main();

What's happening here:

  • We're orchestrating the entire application flow
  • The agent gets built with proper error handling
  • Then we kick off the interactive chat loop so you can start talking to Google Analytics
10

Run the agent

npx ts-node llamaindex-agent.ts

When prompted, authenticate and authorise your agent with Google Analytics, then start asking questions.

Complete Code

Here's the complete code to get you started with Google Analytics and LlamaIndex:

import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";
import { LlamaindexProvider } from "@composio/llamaindex";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) {
    throw new Error("OPENAI_API_KEY is not set in the environment");
  }
if (!COMPOSIO_API_KEY) {
    throw new Error("COMPOSIO_API_KEY is not set in the environment");
  }
if (!COMPOSIO_USER_ID) {
    throw new Error("COMPOSIO_USER_ID is not set in the environment");
  }

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["google_analytics"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
    description:
      "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Google Analytics actions." ,
    llm,
    tools,
  });

  return agent;
}

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err: any) {
    console.error("Failed to start agent:", err?.message ?? err);
    process.exit(1);
  }
}

main();

Conclusion

You've successfully connected Google Analytics to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Google Analytics tools through an MCP endpoint
  • LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
  • The agent becomes more capable without increasing prompt size
  • Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.
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

LangChain logo

LangChain

Use Google Analytics MCP with LangChain

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

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. LlamaIndex 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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