What is Google Analytics Mcp

google-analytics-mcp is a server designed to connect Google Analytics 4 data with various MCP clients like Claude and Cursor, allowing users to query website traffic and user behavior using natural language with access to over 200 dimensions and metrics.

Use cases

Use cases for google-analytics-mcp include generating reports on website traffic, analyzing user engagement metrics, and providing insights for marketing strategies based on user behavior data.

How to use

To use google-analytics-mcp, ensure you have Python 3.8 or higher installed, set up a Google Analytics property with data, and create a service account with access to the Analytics Reporting API. Follow the setup instructions in the README to connect and query your data.

Key features

Key features of google-analytics-mcp include natural language querying capabilities, compatibility with multiple MCP clients, and access to a wide range of GA4 dimensions and metrics for in-depth analysis.

Where to use

google-analytics-mcp can be used in various fields such as digital marketing, web analytics, and business intelligence, where understanding user behavior and website performance is crucial.

Google Analytics MCP Server

Connect Google Analytics 4 data to Claude, Cursor and other MCP clients. Query your website traffic, user behavior, and analytics data in natural language with access to 200+ GA4 dimensions and metrics.

Compatible with: Claude, Cursor and other MCP clients.

I also built a Google Search Console MCP that enables you to mix & match the data from both the sources

Prerequisites

Check your Python setup:

# Check Python version (need 3.10+)
python --version
python3 --version

# Check pip
pip --version
pip3 --version

Required:

• Python 3.10 or higher
• Google Analytics 4 property with data
• Service account with Analytics Reporting API access

Step 1: Setup Google Analytics Credentials

Create Service Account in Google Cloud Console

1. Go to Google Cloud Console
2. Create or select a project:
   • New project: Click “New Project” → Enter project name → Create
   • Existing project: Select from dropdown
3. Enable the Analytics APIs:
   • Go to “APIs & Services” → “Library”
   • Search for “Google Analytics Reporting API” → Click “Enable”
   • Search for “Google Analytics Data API” → Click “Enable”
4. Create Service Account:
   • Go to “APIs & Services” → “Credentials”
   • Click “Create Credentials” → “Service Account”
   • Enter name (e.g., “ga4-mcp-server”)
   • Click “Create and Continue”
   • Skip role assignment → Click “Done”
5. Download JSON Key:
   • Click your service account
   • Go to “Keys” tab → “Add Key” → “Create New Key”
   • Select “JSON” → Click “Create”
   • Save the JSON file - you’ll need its path

Add Service Account to GA4

1. Get service account email:
   • Open the JSON file
   • Find the client_email field
   • Copy the email (format: [email protected])
2. Add to GA4 property:
   • Go to Google Analytics
   • Select your GA4 property
   • Click “Admin” (gear icon at bottom left)
   • Under “Property” → Click “Property access management”
   • Click “+” → “Add users”
   • Paste the service account email
   • Select “Viewer” role
   • Uncheck “Notify new users by email”
   • Click “Add”

Find Your GA4 Property ID

1. In Google Analytics, select your property
2. Click “Admin” (gear icon)
3. Under “Property” → Click “Property details”
4. Copy the Property ID (numeric, e.g., 123456789)
   • Note: This is different from the “Measurement ID” (starts with G-)

Test Your Setup (Optional)

Verify your credentials:

pip install google-analytics-data

Create a test script (test_ga4.py):

import os
from google.analytics.data_v1beta import BetaAnalyticsDataClient

# Set credentials path
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "/path/to/your/service-account-key.json"

# Test connection
client = BetaAnalyticsDataClient()
print("✅ GA4 credentials working!")

Run the test:

python test_ga4.py

If you see “✅ GA4 credentials working!” you’re ready to proceed.

Step 2: Install the MCP Server

Choose one method:

Method A: pip install (Recommended)

pip install google-analytics-mcp

MCP Configuration:

First, check your Python command:

python3 --version
python --version

Then use the appropriate configuration:

If python3 --version worked:

{
  "mcpServers": {
    "ga4-analytics": {
      "command": "python3",
      "args": [
        "-m",
        "ga4_mcp_server"
      ],
      "env": {
        "GOOGLE_APPLICATION_CREDENTIALS": "/path/to/your/service-account-key.json",
        "GA4_PROPERTY_ID": "123456789"
      }
    }
  }
}

If python --version worked:

{
  "mcpServers": {
    "ga4-analytics": {
      "command": "python",
      "args": [
        "-m",
        "ga4_mcp_server"
      ],
      "env": {
        "GOOGLE_APPLICATION_CREDENTIALS": "/path/to/your/service-account-key.json",
        "GA4_PROPERTY_ID": "123456789"
      }
    }
  }
}

Method B: GitHub download

git clone https://github.com/surendranb/google-analytics-mcp.git
cd google-analytics-mcp
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

MCP Configuration:

{
  "mcpServers": {
    "ga4-analytics": {
      "command": "/full/path/to/ga4-mcp-server/venv/bin/python",
      "args": [
        "/full/path/to/ga4-mcp-server/ga4_mcp_server.py"
      ],
      "env": {
        "GOOGLE_APPLICATION_CREDENTIALS": "/path/to/your/service-account-key.json",
        "GA4_PROPERTY_ID": "123456789"
      }
    }
  }
}

Step 3: Update Configuration

Replace these placeholders in your MCP configuration:

• /path/to/your/service-account-key.json with your JSON file path
• 123456789 with your GA4 Property ID
• /full/path/to/ga4-mcp-server/ with your download path (Method B only)

Usage

Once configured, ask your MCP client questions like:

Discovery & Exploration

• What GA4 dimension categories are available?
• Show me all ecommerce metrics
• What dimensions can I use for geographic analysis?

Traffic Analysis

• What’s my website traffic for the past week?
• Show me user metrics by city for last month
• Compare bounce rates between different date ranges

Multi-Dimensional Analysis

• Show me revenue by country and device category for last 30 days
• Analyze sessions and conversions by campaign and source/medium
• Compare user engagement across different page paths and traffic sources

E-commerce Analysis

• What are my top-performing products by revenue?
• Show me conversion rates by traffic source and device type
• Analyze purchase behavior by user demographics

Quick Start Examples

Try these example queries to see the MCP’s analytical capabilities:

1. Geographic Distribution

Show me a map of visitors by city for the last 30 days, with a breakdown of new vs returning users

This demonstrates:

• Geographic analysis
• User segmentation
• Time-based filtering
• Data visualization

2. User Behavior Analysis

Compare average session duration and pages per session by device category and browser over the last 90 days

This demonstrates:

• Multi-dimensional analysis
• Time series comparison
• User engagement metrics
• Technology segmentation

3. Traffic Source Performance

Show me conversion rates and revenue by traffic source and campaign, comparing last 30 days vs previous 30 days

This demonstrates:

• Marketing performance analysis
• Period-over-period comparison
• Conversion tracking
• Revenue attribution

4. Content Performance

What are my top 10 pages by engagement rate, and how has their performance changed over the last 3 months?

This demonstrates:

• Content analysis
• Trend analysis
• Engagement metrics
• Ranking and sorting

Available Tools

The server provides 5 main tools:

1. get_ga4_data - Retrieve GA4 data with custom dimensions and metrics
2. list_dimension_categories - Browse available dimension categories
3. list_metric_categories - Browse available metric categories
4. get_dimensions_by_category - Get dimensions for a specific category
5. get_metrics_by_category - Get metrics for a specific category

Dimensions & Metrics

Access to 200+ GA4 dimensions and metrics organized by category:

Dimension Categories

• Time: date, hour, month, year, etc.
• Geography: country, city, region
• Technology: browser, device, operating system
• Traffic Source: campaign, source, medium, channel groups
• Content: page paths, titles, content groups
• E-commerce: item details, transaction info
• User Demographics: age, gender, language
• Google Ads: campaign, ad group, keyword data
• And 10+ more categories

Metric Categories

• User Metrics: totalUsers, newUsers, activeUsers
• Session Metrics: sessions, bounceRate, engagementRate
• E-commerce: totalRevenue, transactions, conversions
• Events: eventCount, conversions, event values
• Advertising: adRevenue, returnOnAdSpend
• And more specialized metrics

Troubleshooting

If you get “No module named ga4_mcp_server” (Method A):

pip3 install --user google-analytics-mcp

If you get “executable file not found”:

• Try the other Python command (python vs python3)
• Use pip3 instead of pip if needed

Permission errors:

# Try user install instead of system-wide
pip install --user google-analytics-mcp

Credentials not working:

1. Verify the JSON file path is correct and accessible
2. Check service account permissions:
   • Go to Google Cloud Console → IAM & Admin → IAM
   • Find your service account → Check permissions
3. Verify GA4 access:
   • GA4 → Admin → Property access management
   • Check for your service account email
4. Verify ID type:
   • Property ID: numeric (e.g., 123456789) ✅
   • Measurement ID: starts with G- (e.g., G-XXXXXXXXXX) ❌

API quota/rate limit errors:

• GA4 has daily quotas and rate limits
• Try reducing the date range in your queries
• Wait a few minutes between large requests

Project Structure

google-analytics-mcp/
├── ga4_mcp_server.py       # Main MCP server
├── ga4_dimensions.json     # All available GA4 dimensions
├── ga4_metrics.json        # All available GA4 metrics
├── requirements.txt        # Python dependencies
├── pyproject.toml          # Package configuration
├── README.md               # This file
└── claude-config-template.json  # MCP configuration template

License

MIT License