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Google Analytics MCP Server

PyPI version Python 3.10+ GitHub branch check runs PyPI - Downloads GitHub stars GitHub forks YouTube Video Views

This repo contains the source code for running a local MCP server that interacts with APIs for Google Analytics.

Join the discussion and ask questions in the 🤖-analytics-mcp channel on Discord.

Tools 🛠️

The server uses the Google Analytics Admin API and Google Analytics Data API to provide several Tools for use with LLMs.

Retrieve account and property information 🟠

  • get_account_summaries: Retrieves information about the user's Google Analytics accounts and properties.
  • get_property_details: Returns details about a property.
  • list_google_ads_links: Returns a list of links to Google Ads accounts for a property.
  • list_property_annotations: Returns annotations for a property.
  • create_property_annotation: Creates an annotation for a property (requires passing the --allow-write flag and the analytics.edit scope).

Run core reports 📙

  • run_report: Runs a Google Analytics report using the Data API.
  • run_funnel_report: Runs a Google Analytics funnel report using the Data API.
  • get_custom_dimensions_and_metrics: Retrieves the custom dimensions and metrics for a specific property.

Run realtime reports ⏳

  • run_realtime_report: Runs a Google Analytics realtime report using the Data API.

Setup instructions 🔧

✨ Watch the Google Analytics MCP Setup Tutorial on YouTube for a step-by-step walkthrough of these instructions.

Watch the video

Setup involves the following steps:

  1. Configure Python.
  2. Configure credentials for Google Analytics.
  3. Configure Gemini.

Configure Python 🐍

Install pipx.

Enable APIs in your project ✅

Follow the instructions to enable the following APIs in your Google Cloud project:

Configure credentials 🔑

Configure your Application Default Credentials (ADC). Make sure the credentials are for a user with access to your Google Analytics accounts or properties.

Credentials must include the Google Analytics read-only scope:

https://www.googleapis.com/auth/analytics.readonly

If you plan to enable write tools (such as create_property_annotation) using the --allow-write flag, your credentials must also include the edit scope:

https://www.googleapis.com/auth/analytics.edit

Check out Manage OAuth Clients for how to create an OAuth client.

Here are some sample gcloud commands you might find useful:

  • Set up ADC using user credentials and an OAuth desktop or web client after downloading the client JSON to YOUR_CLIENT_JSON_FILE.

    gcloud auth application-default login \
      --scopes https://www.googleapis.com/auth/analytics.readonly,https://www.googleapis.com/auth/cloud-platform \
      --client-id-file=YOUR_CLIENT_JSON_FILE
    
  • Set up ADC using service account impersonation.

    gcloud auth application-default login \
      --impersonate-service-account=SERVICE_ACCOUNT_EMAIL \
      --scopes=https://www.googleapis.com/auth/analytics.readonly,https://www.googleapis.com/auth/cloud-platform
    

When the gcloud auth application-default command completes, copy the PATH_TO_CREDENTIALS_JSON file location printed to the console in the following message. You'll need this for the next step!

Credentials saved to file: [PATH_TO_CREDENTIALS_JSON]

Configure Gemini

  1. Install Gemini CLI or Gemini Code Assist.

  2. Create or edit the file at ~/.gemini/settings.json, adding your server to the mcpServers list.

    Replace PATH_TO_CREDENTIALS_JSON with the path you copied in the previous step.

    We also recommend that you add a GOOGLE_CLOUD_PROJECT attribute to the env object. Replace YOUR_PROJECT_ID in the following example with the project ID of your Google Cloud project.

    {
      "mcpServers": {
        "analytics-mcp": {
          "command": "pipx",
          "args": ["run", "analytics-mcp"],
          "env": {
            "GOOGLE_APPLICATION_CREDENTIALS": "PATH_TO_CREDENTIALS_JSON",
            "GOOGLE_CLOUD_PROJECT": "YOUR_PROJECT_ID"
          }
        }
      }
    }
    

    To enable write tools (e.g. create_property_annotation), append "--allow-write" to "args": ["run", "analytics-mcp", "--allow-write"].

Configure Claude Code

  1. Add the MCP server with the following command:

    Replace PATH_TO_CREDENTIALS_JSON with the path you copied in the previous step, and replace YOUR_PROJECT_ID with the project ID of your Google Cloud project.

    claude mcp add analytics-mcp \
      --scope user \
      -e "GOOGLE_APPLICATION_CREDENTIALS=PATH_TO_CREDENTIALS_JSON" \
      -e "GOOGLE_CLOUD_PROJECT=YOUR_PROJECT_ID" \
      -- pipx run analytics-mcp
    

Multi-tenant HTTP & End-User OAuth 🌐

To host analytics-mcp as a shared multi-tenant HTTP service (where each end user signs in with their own Google account via OAuth 2.0 rather than using server-side Application Default Credentials), start the server with --transport http:

pipx run analytics-mcp \
  --transport http --stateless-http --host 0.0.0.0 --port 8080
  • Agent Framework OAuth (e.g. Google ADK): Configure per-user Google OAuth on McpToolset so end users are automatically prompted with a Sign in button in the chat UI, and can even combine Google Analytics MCP alongside other MCP servers in the same agent. Paired with --stateless-http, this mode is completely stateless and horizontally scalable across multiple replicas.

  • Native MCP OAuth 2.1 Server (--oauth): Pass --oauth (with GOOGLE_OAUTH_CLIENT_ID, GOOGLE_OAUTH_CLIENT_SECRET, and optional ANALYTICS_MCP_ISSUER_URL set) to enable the built-in MCP OAuth 2.1 Authorization Server:

    export GOOGLE_OAUTH_CLIENT_ID="your-client-id.apps.googleusercontent.com"
    export GOOGLE_OAUTH_CLIENT_SECRET="your-client-secret"
    export ANALYTICS_MCP_ISSUER_URL="https://analytics-mcp.yourdomain.com"
    
    pipx run analytics-mcp \
      --transport http --stateless-http --oauth --host 0.0.0.0 --port 8080
    

    Note: The built-in --oauth provider stores dynamic client registrations, pending authorization state, and refresh tokens in process memory (run as a single instance or with sticky sessions; restarts require re-authentication).

See the complete walkthrough, Dockerfile, and runnable agent code in examples/multi_tenant_adk_agent/README.md.

Try it out 🥼

Launch Gemini Code Assist or Gemini CLI and type /mcp. You should see analytics-mcp listed in the results.

Here are some sample prompts to get you started:

  • Ask what the server can do:

    what can the analytics-mcp server do?
    
  • Ask about a Google Analytics property

    Give me details about my Google Analytics property with 'xyz' in the name
    
  • Prompt for analysis:

    what are the most popular events in my Google Analytics property in the last 180 days?
    
  • Ask about signed-in users:

    were most of my users in the last 6 months logged in?
    
  • Ask about property configuration:

    what are the custom dimensions and custom metrics in my property?
    

Contributing ✨

Contributions welcome! See the Contributing Guide.

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