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Google Analytics MCP 服务器

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ruchernchong

Model Context Protocol server for Google Analytics, enabling LLMs to fetch and analyze web analytics data

Publisherruchernchong
Repositorymcp-server-google-analytics
LanguageJavaScript
Forks
17
Stars
72
Available tools
0
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    Google Analytics MCP 服务器 exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    72 stars and 17 forks from the linked repository.

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Google Analytics MCP Server

smithery badge

An MCP server implementation for accessing Google Analytics 4 (GA4) data, built using the Model Context Protocol TypeScript SDK.

Features

  • Get page view metrics with customizable dimensions
  • Track active and new users over time
  • Analyze specific events and their metrics
  • Monitor user behavior metrics (session duration, bounce rate)
  • Flexible date range selection for all queries

Prerequisites

  • Node.js 20 or higher
  • A Google Analytics 4 property.
  • A Google Cloud project with the Analytics Data API enabled.
  • A service account with credentials to access the API.

Setup and Configuration

To use this server, you need to configure authentication with Google Analytics. This is done using a service account.

1. Enable the Google Analytics Data API

  1. Go to the Google Cloud Console.
  2. Select the project you want to use.
  3. In the navigation menu, go to APIs & Services > Library.
  4. Search for "Google Analytics Data API" and enable it.

2. Create a Service Account

  1. In the Google Cloud Console, navigate to IAM & Admin > Service Accounts.
  2. Click "Create Service Account".
  3. Give the service account a name (e.g., "GA4 MCP Server").
  4. Click "Create and Continue".
  5. You can skip granting the service account access to the project.
  6. Click "Done".
  7. Find the service account you just created and click on the three dots under "Actions".
  8. Select "Manage keys", then "Add Key" > "Create new key".
  9. Choose JSON as the key type and click "Create". A JSON file with the credentials will be downloaded.

3. Grant Service Account Access to Google Analytics

  1. Open Google Analytics.
  2. Navigate to the Admin section of your GA4 property.
  3. Under the Property column, click on Property Access Management.
  4. Click the "+" button to add a new user.
  5. In the "Email address" field, paste the client_email from the JSON credentials file you downloaded.
  6. Assign the "Viewer" role. You do not need to notify the user.
  7. Click "Add".

4. Set Environment Variables

The server requires the following environment variables:

  • GOOGLE_CLIENT_EMAIL: The client_email from your service account JSON file.
  • GOOGLE_PRIVATE_KEY: The private_key from your service account JSON file.
  • GA_PROPERTY_ID: Your Google Analytics 4 property ID.

You can set them in your environment or use a .env file.

bash
export GOOGLE_CLIENT_EMAIL="your-service-account@your-project.iam.gserviceaccount.com"
export GOOGLE_PRIVATE_KEY="-----BEGIN PRIVATE KEY-----\nYOUR_PRIVATE_KEY\n-----END PRIVATE KEY-----\n"
export GA_PROPERTY_ID="your_property_id"

Installation

Installing via Smithery

To install Google Analytics Server for Claude Desktop automatically via Smithery:

bash
npx -y @smithery/cli install mcp-server-google-analytics --client claude

Manual Installation

bash
npm install -g mcp-server-google-analytics

Or use with npx directly:

bash
npx mcp-server-google-analytics

Usage

Starting the Server

bash
pnpm start

Configuration in Claude Desktop

Add this to your Claude Desktop configuration:

json
{
  "mcpServers": {
    "google-analytics": {
      "command": "npx",
      "args": ["-y", "mcp-server-google-analytics"],
      "env": {
        "GOOGLE_CLIENT_EMAIL": "your-service-account@project.iam.gserviceaccount.com",
        "GOOGLE_PRIVATE_KEY": "your-private-key",
        "GA_PROPERTY_ID": "your-ga4-property-id"
      }
    }
  }
}

Available Functions

runReport

Run a flexible report to get analytics data.

Input:

json
{
  "startDate": "2024-01-01",
  "endDate": "2024-01-31",
  "dimensions": [{ "name": "country" }, { "name": "city" }],
  "metrics": [{ "name": "activeUsers" }, { "name": "newUsers" }],
  "dimensionFilter": {
    "filter": {
      "fieldName": "country",
      "stringFilter": {
        "value": "United States"
      }
    }
  }
}

getPageViews

Get page view metrics for a specific date range:

json
{
  "startDate": "2024-01-01",
  "endDate": "2024-01-31",
  "dimensions": ["page", "country"] // Optional
}

getActiveUsers

Get active users metrics:

json
{
  "startDate": "2024-01-01",
  "endDate": "2024-01-31"
}

getEvents

Get event metrics:

json
{
  "startDate": "2024-01-01",
  "endDate": "2024-01-31",
  "eventName": "purchase" // Optional
}

getUserBehavior

Get user behavior metrics:

json
{
  "startDate": "2024-01-01",
  "endDate": "2024-01-31"
}

Security Considerations

  • Least Privilege: Only grant the service account the "Viewer" role in Google Analytics.
  • Key Management: Keep your service account key file secure and do not expose it in client-side code.
  • Environment Variables: Use environment variables to store sensitive information like the client email, private key, and property ID.

Contributing

Contributions are welcome! Please read our Contributing Guide for details on our code of conduct and the process for submitting pull requests.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "ruchernchong-mcp-server-google-analytics": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-server-google-analytics"
      ]
    }
  }
}

Use Google Analytics MCP 服务器 MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Google Analytics MCP 服务器 is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Google Analytics MCP 服务器 as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Google Analytics MCP 服务器 MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "ruchernchong-mcp-server-google-analytics": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-server-google-analytics"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Google Analytics MCP 服务器 MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Google Analytics MCP 服务器 MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Google Analytics MCP 服务器 to help me with this task?
Google Analytics MCP 服务器
Sure. I read it.
Here is what I found using Google Analytics MCP 服务器.

Frequently asked questions

What is the Google Analytics MCP 服务器 MCP server used for?

Google Analytics MCP 服务器 is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Google Analytics MCP 服务器 MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Google Analytics MCP 服务器 with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Google Analytics MCP 服务器 MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Google Analytics MCP 服务器 connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Google Analytics MCP 服务器 MCP to TypingMind?

Google Analytics MCP 服务器 runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Google Analytics MCP 服务器 MCP provide in TypingMind?

Google Analytics MCP 服务器 exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Google Analytics MCP 服务器 MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Google Analytics MCP 服务器 requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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