Provides comprehensive access to Google Analytics 4 data, enabling AI agents to retrieve historical reports for traffic, acquisition, and page performance, monitor real-time user activity, and manage property-level metadata and custom dimensions.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Google Analytics MCP ServerShow me a traffic summary for the last 30 days"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Google Analytics MCP Server
A FastMCP server that provides AI agents with comprehensive access to Google Analytics 4 data via the Model Context Protocol (MCP).
Features
18 MCP tools covering all aspects of Google Analytics 4
HTTP streaming transport for scalable deployments
Service account authentication for automated server-to-server access
Dynamic property discovery across all accessible GA4 accounts
Historical reports with flexible dimensions, metrics, and date ranges
Realtime data for current user activity
Custom dimensions/metrics support
Installation
# Clone the repository
git clone <repo-url>
cd google-analytics-mcp
# Install dependencies with uv
uv syncConfiguration
Environment Variables
Variable | Required | Default | Description |
| Yes* | - | Path to service account JSON file |
| No |
| Host to bind the server |
| No |
| Port for the server |
*Can also use Application Default Credentials (ADC) via gcloud auth application-default login
Google Cloud Setup
Step 1: Create a Google Cloud Project (if you don't have one)
Go to the Google Cloud Console
Click the project dropdown at the top of the page
Click New Project
Enter a project name (e.g., "GA MCP Server")
Click Create
Wait for the project to be created, then select it from the project dropdown
Step 2: Enable Required APIs
In the Google Cloud Console, go to APIs & Services > Library
Search for and enable these APIs:
Google Analytics Data API - for running reports
Google Analytics Admin API - for listing properties
For each API:
Click on the API name
Click Enable
Step 3: Create a Service Account
In the Google Cloud Console, go to IAM & Admin > Service Accounts
Click + Create Service Account at the top
Fill in the details:
Service account name:
ga-mcp-serverService account ID: (auto-filled based on name)
Description: "Service account for Google Analytics MCP Server"
Click Create and Continue
Skip the optional "Grant this service account access" step (click Continue)
Skip the optional "Grant users access" step (click Done)
Step 4: Create and Download the Credentials JSON Key
In the Service Accounts list, find your newly created service account
Click on the service account email to open its details
Go to the Keys tab
Click Add Key > Create new key
Select JSON as the key type
Click Create
The JSON key file will automatically download to your computer
Important: Move this file to a secure location and note the path
# Example: move to your project directory mv ~/Downloads/your-project-xxxxx.json ./credentials.json
Security Warning: This JSON file contains sensitive credentials. Never commit it to version control or share it publicly.
Step 5: Grant the Service Account Access to Google Analytics
The service account needs explicit access to your GA4 properties. Without this step, list_properties will return an empty list.
Find your service account email:
Find your service account and copy the email address
It looks like:
ga-mcp-server@your-project.iam.gserviceaccount.com
Grant access in Google Analytics:
Go to Google Analytics
Click the Admin gear icon (bottom left corner)
Choose where to grant access:
Option A: Account Level (recommended) - Grants access to ALL properties under the account:
In the Account column, click Account Access Management
Option B: Property Level - Grants access to a specific property only:
First select the property from the Property dropdown
In the Property column, click Property Access Management
Click the + button in the top right
Select Add users
In the "Email addresses" field, paste your service account email
Under "Direct roles and data restrictions":
Select Viewer (sufficient for reading all analytics data)
Leave data restrictions unchecked for full access
Click Add
Verify access was granted:
The service account email should now appear in the users list
You can test by calling
list_properties- it should return your properties
Note: It may take a few minutes for permissions to propagate. If
list_propertiesstill returns empty, wait 2-3 minutes and try again.
Step 6: Set the Environment Variable
# Option 1: Set for current terminal session
export GOOGLE_APPLICATION_CREDENTIALS=/path/to/credentials.json
# Option 2: Add to your shell profile (~/.bashrc, ~/.zshrc, etc.)
echo 'export GOOGLE_APPLICATION_CREDENTIALS=/path/to/credentials.json' >> ~/.bashrc
source ~/.bashrc
# Option 3: Create a .env file in the project directory
cp .env.example .env
# Then edit .env and set the path to your credentials fileAlternative: Using Application Default Credentials (ADC)
If you prefer not to use a service account, you can authenticate with your personal Google account:
gcloud auth application-default login \
--scopes=https://www.googleapis.com/auth/analytics.readonlyThis is useful for local development but not recommended for production deployments.
Usage
Running the Server
# Using uv
uv run python main.py
# Or directly
python main.pyThe server starts on http://0.0.0.0:8000 by default.
MCP Client Configuration
Add to your MCP client configuration (e.g., Claude Desktop):
{
"mcpServers": {
"google-analytics": {
"url": "http://localhost:8000/mcp"
}
}
}Available Tools
Discovery Tools
Tool | Description |
| List all accessible GA4 properties |
| Get property info (timezone, currency, etc.) |
| Get all dimensions/metrics for a property |
Historical Report Tools
Tool | Description |
| Flexible report with any dimensions/metrics |
| Daily users, sessions, pageviews, bounce rate |
| Traffic sources breakdown |
| Top pages by pageviews |
| Users by country/city |
| Desktop/mobile/tablet breakdown |
| Top events by count |
| Period-over-period comparison |
Realtime Tools
Tool | Description |
| Current active users overview |
| Currently active pages |
| Current traffic sources |
| Events occurring now |
| Custom realtime query |
Admin Tools
Tool | Description |
| Property's custom dimensions |
| Property's custom metrics |
Example Usage (AI Agent)
1. list_properties()
-> Discover all accessible GA4 properties
2. get_property_details("123456789")
-> Get timezone, currency, and other property metadata
3. get_traffic_summary("123456789", "7daysAgo", "today")
-> Get daily traffic metrics for the last week
4. get_acquisition_report("123456789", "yesterday", "yesterday")
-> See where yesterday's traffic came from
5. compare_periods("123456789", "7daysAgo", "today", "14daysAgo", "8daysAgo")
-> Compare this week to last week
6. get_realtime_overview("123456789")
-> See who's on the site right nowProject Structure
google-analytics-mcp/
├── pyproject.toml # Dependencies and build config
├── main.py # Server entry point
├── src/
│ ├── __init__.py
│ ├── config.py # Environment variable settings
│ ├── clients/
│ │ ├── __init__.py
│ │ ├── admin_client.py # GA Admin API wrapper
│ │ └── data_client.py # GA Data API wrapper
│ └── tools/
│ ├── __init__.py
│ ├── discovery.py # Property discovery tools
│ ├── reports.py # Historical report tools
│ ├── realtime.py # Realtime data tools
│ └── admin.py # Custom dimensions/metricsLicense
MIT
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