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google-analytics-mcp

Google Analytics 4 MCP Server - Access GA4 data in Claude, Cursor and other MCP clients

1.0.10
PyPI
Maintainers
1

Google Analytics MCP Logo

Google Analytics MCP Server

PyPI version PyPI Downloads GitHub stars GitHub forks Python 3.10+ License: MIT Made with Love

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

  • Go to Google Cloud Console
  • Create or select a project:
    • New project: Click "New Project" → Enter project name → Create
    • Existing project: Select from dropdown
  • 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"
  • 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"
  • 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

  • Get service account email:
    • Open the JSON file
    • Find the client_email field
    • Copy the email (format: ga4-mcp-server@your-project.iam.gserviceaccount.com)
  • 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

  • In Google Analytics, select your property
  • Click "Admin" (gear icon)
  • Under "Property" → Click "Property details"
  • 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("āœ… GA4 credentials working!")

Run the test:

python test_ga4.py

If you see "āœ… GA4 credentials working!" you're ready to proceed.

Step 2: Install the MCP Server

Choose one method:

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:

  • get_ga4_data - Retrieve GA4 data with custom dimensions and metrics
  • list_dimension_categories - Browse available dimension categories
  • list_metric_categories - Browse available metric categories
  • get_dimensions_by_category - Get dimensions for a specific category
  • 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:

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

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

License

MIT License

Keywords

google-analytics

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