Google Analytics MCP Server (Experimental)

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

The server supports two deployment modes:

• Local (stdio) — run as a subprocess by Gemini CLI, Claude Desktop, Claude Code, or any MCP client. Uses Application Default Credentials. No extra infrastructure needed.
• Remote (HTTP + OAuth) — deploy to Google Cloud Run and connect from web-based clients such as claude.ai. Users authenticate with their own Google account via OAuth 2.0; no credentials are shared with the server operator. See Remote deployment.

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

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

• 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.

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

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

Setup involves the following steps:

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

Install pipx.

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

• Google Analytics Admin API
• Google Analytics Data API

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

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]

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_PROJECT_ID": "YOUR_PROJECT_ID"
         }
       }
     }
   }

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_PROJECT_ID=YOUR_PROJECT_ID" \
     -- pipx run analytics-mcp

Deploy the server to Cloud Run so web-based MCP clients such as claude.ai can connect to it. Each user authenticates with their own Google account via OAuth 2.0 — no Analytics credentials are configured on the server, and requests without a valid per-user token are rejected.

In addition to the Google Analytics Admin API and Google Analytics Data API, enable:

• Cloud Run Admin API
• Cloud Build API
• Artifact Registry API
• Secret Manager API

1. Open APIs & Services → Credentials in the Google Cloud Console.

2. Click Create credentials → OAuth client ID.

3. Choose Web application as the application type.

4. Under Authorized redirect URIs, add a placeholder for now — you will replace it with the real service URL after deploying:

   https://example.com/auth/callback
   

5. Click Create and note the Client ID and Client secret.

Never pass the OAuth client secret as a plaintext --set-env-vars value — it would be visible to anyone who can describe the Cloud Run service.

printf '%s' 'YOUR_OAUTH_CLIENT_SECRET' | gcloud secrets create \
  analytics-mcp-oauth-client-secret --data-file=-

Run the deploy script, which builds the image with Cloud Build and performs the two-phase Cloud Run deployment (deploy → discover service URL → redeploy with ANALYTICS_MCP_BASE_URL set):

PROJECT_ID=YOUR_PROJECT_ID \
REGION=YOUR_REGION \
OAUTH_CLIENT_ID=YOUR_OAUTH_CLIENT_ID \
  ./deploy/cloud-run.sh

The script prints the service URL when it finishes. Then return to your OAuth client in the Google Cloud Console and replace the placeholder redirect URI with:

https://YOUR_SERVICE_URL/auth/callback

The service is deployed with --allow-unauthenticated because authentication happens at the application layer: FastMCP's Google OAuth provider rejects any request to /mcp that doesn't carry a valid per-user token.

1. Open claude.ai and go to Settings → Connectors.

2. Add a custom connector with the URL:

   https://YOUR_SERVICE_URL/mcp
   

3. Authorize with your Google account when prompted.

When ANALYTICS_MCP_OAUTH_CLIENT_ID and ANALYTICS_MCP_OAUTH_CLIENT_SECRET are both set, the server starts in HTTP mode with OAuth and serves /mcp. Otherwise it runs on stdio exactly as before — local setups are unaffected.

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?
  

Contributions welcome! See the Contributing Guide.