Google Analytics MCP Server
Enables AI agents to interact with Google Analytics 4 data, providing tools for historical reporting, real-time activity monitoring, and property management. It supports secure service account authentication to access metrics like traffic summaries, user acquisition, and custom dimensions.
README
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 sync
Configuration
Environment Variables
| Variable | Required | Default | Description |
|---|---|---|---|
GOOGLE_APPLICATION_CREDENTIALS |
Yes* | - | Path to service account JSON file |
MCP_HOST |
No | 0.0.0.0 |
Host to bind the server |
MCP_PORT |
No | 8000 |
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-server - Service account ID: (auto-filled based on name)
- Description: "Service account for Google Analytics MCP Server"
- Service account name:
- 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:
- Go to Google Cloud Console > IAM & Admin > Service Accounts
- Find your service account and copy the email address
- It looks like:
ga-mcp-server@your-project.iam.gserviceaccount.com
- It looks like:
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 file
Alternative: 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.readonly
This 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.py
The 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_properties |
List all accessible GA4 properties |
get_property_details |
Get property info (timezone, currency, etc.) |
get_available_metrics |
Get all dimensions/metrics for a property |
Historical Report Tools
| Tool | Description |
|---|---|
run_custom_report |
Flexible report with any dimensions/metrics |
get_traffic_summary |
Daily users, sessions, pageviews, bounce rate |
get_acquisition_report |
Traffic sources breakdown |
get_page_performance |
Top pages by pageviews |
get_geographic_report |
Users by country/city |
get_device_report |
Desktop/mobile/tablet breakdown |
get_events_report |
Top events by count |
compare_periods |
Period-over-period comparison |
Realtime Tools
| Tool | Description |
|---|---|
get_realtime_overview |
Current active users overview |
get_realtime_pages |
Currently active pages |
get_realtime_traffic_sources |
Current traffic sources |
get_realtime_events |
Events occurring now |
run_custom_realtime_report |
Custom realtime query |
Admin Tools
| Tool | Description |
|---|---|
list_custom_dimensions |
Property's custom dimensions |
list_custom_metrics |
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 now
Project 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/metrics
License
MIT
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