Google Analytics MCP Server

Google Analytics MCP Server (Experimental)

[](https://pypi.org/project/analytics-mcp/)

[](https://www.python.org/downloads/)

[](https://github.com/googleanalytics/google-analytics-mcp/actions?query=branch%3Amain++)

[](https://pypi.org/project/analytics-mcp/)

[](https://github.com/googleanalytics/google-analytics-mcp/stargazers)

[](https://github.com/googleanalytics/google-analytics-mcp/network/members)

[](https://www.youtube.com/watch?v=PT4wGPxWiRQ)

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](https://youtu.be/nS8HLdwmVlY) on YouTube for a step-by-step

walkthrough of these instructions.

[](https://www.youtube.com/watch?v=nS8HLdwmVlY)

Setup involves the following steps:

• Configure Python.
• Configure credentials for Google Analytics.
• Configure Gemini.

Configure Python 🐍

Install pipx ↗.

Enable APIs in your project ✅

Follow the instructions ↗

to enable the following APIs in your Google Cloud project:

• Google Analytics Admin API ↗
• Google Analytics Data API ↗

Configure credentials 🔑

Configure your [Application Default Credentials

(ADC)](https://cloud.google.com/docs/authentication/provide-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

• Install [Gemini

CLI](https://github.com/google-gemini/gemini-cli/blob/main/docs/get-started/installation.md)

or [Gemini Code

Assist](https://marketplace.visualstudio.com/items?itemName=Google.geminicodeassist).

• 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"
          }
        }
      }
    }

To enable write tools (e.g. create_property_annotation), append

"--allow-write" to "args": ["run", "analytics-mcp", "--allow-write"].

Configure Claude Code

• 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

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 ↗.