Provides access to Google Ads data within Google Analytics 4, allowing queries about campaign, ad group, and keyword performance.
Connects to Google Analytics 4 data, enabling natural language queries about website traffic, user behavior, and analytics with access to 200+ GA4 dimensions and metrics.
Uses Google Cloud for service account creation and API access to connect with Google Analytics data.
Google Analytics MCP Server
mcp-name: io.github.surendranb/google-analytics-mcp
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:
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 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
fieldCopy 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:
Create a test script (test_ga4.py
):
Run the test:
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)
MCP Configuration:
First, check your Python command:
Then use the appropriate configuration:
If python3 --version
worked:
If python --version
worked:
Method B: GitHub download
MCP Configuration:
Step 3: Update Configuration
Replace these placeholders in your MCP configuration:
/path/to/your/service-account-key.json
with your JSON file path123456789
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
This demonstrates:
Geographic analysis
User segmentation
Time-based filtering
Data visualization
2. User Behavior Analysis
This demonstrates:
Multi-dimensional analysis
Time series comparison
User engagement metrics
Technology segmentation
3. Traffic Source Performance
This demonstrates:
Marketing performance analysis
Period-over-period comparison
Conversion tracking
Revenue attribution
4. Content Performance
This demonstrates:
Content analysis
Trend analysis
Engagement metrics
Ranking and sorting
🚀 Performance Optimizations
This MCP server includes built-in optimizations to prevent context window crashes and ensure smooth operation:
Smart Data Volume Management
Automatic row estimation - Checks data volume before fetching
Interactive warnings - Alerts when queries would return >2,500 rows
Optimization suggestions - Provides specific recommendations to reduce data volume
Server-Side Processing
Intelligent aggregation - Automatically aggregates data when beneficial (e.g., totals across time periods)
Smart sorting - Returns most relevant data first (recent dates, highest values)
Efficient filtering - Leverages GA4's server-side filtering capabilities
User Control Parameters
limit
- Set maximum number of rows to returnproceed_with_large_dataset=True
- Override warnings for large datasetsenable_aggregation=False
- Disable automatic aggregationestimate_only=True
- Get row count estimates without fetching data
Example: Handling Large Datasets
Available Tools
The server provides 5 main tools with built-in optimization to prevent context window crashes:
get_ga4_data
- Retrieve GA4 data with custom dimensions and metricsSmart data volume warnings - Alerts when queries would return >2,500 rows
Server-side aggregation - Automatically aggregates data when beneficial
Intelligent sorting - Returns most relevant data first
User control parameters -
limit
,proceed_with_large_dataset
,enable_aggregation
list_dimension_categories
- Browse available dimension categorieslist_metric_categories
- Browse available metric categoriesget_dimensions_by_category
- Get dimensions for a specific categoryget_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):
If you get "executable file not found":
Try the other Python command (
python
vspython3
)Use
pip3
instead ofpip
if needed
Permission errors:
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
) ✅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
License
MIT License
This server cannot be installed
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
Connects Google Analytics 4 data to Claude, Cursor and other MCP clients, enabling natural language queries of website traffic, user behavior, and analytics data with access to 200+ GA4 dimensions and metrics.
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