Content
# MCP Server for Google Analytics 4
A Model Context Protocol (MCP) server that allows Large Language Models (LLMs) to interact with Google Analytics 4 (GA4) data through the Google Analytics Data API.
## Features
- Run standard GA4 reports with customizable dimensions, metrics, and date ranges
- Get real-time data for the past 30 minutes
- Retrieve metadata about available metrics and dimensions
- Secure authentication using Google Cloud's Application Default Credentials
- Configurable for easy deployment via [Smithery](https://smithery.ai)
## Installation
### Using pip
```bash
pip install mcp-server-ga4
```
### From source
```bash
git clone https://github.com/yourusername/mcp-server-ga4.git
cd mcp-server-ga4
pip install -e .
```
## Authentication
This server uses Google Cloud's Application Default Credentials (ADC) for authentication. Before using the server, you'll need to:
1. [Create a Google Cloud project](https://cloud.google.com/resource-manager/docs/creating-managing-projects)
2. [Enable the Google Analytics Data API](https://console.cloud.google.com/flows/enableapi?apiid=analyticsdata.googleapis.com)
3. Set up authentication:
```bash
gcloud auth application-default login
```
For more details, see the [Google Cloud Authentication documentation](https://cloud.google.com/docs/authentication/provide-credentials-adc).
## Usage
### Command Line
Start the server with your GA4 property ID:
```bash
mcp-server-ga4 --property-id YOUR_GA4_PROPERTY_ID
```
The server will use the standard MCP stdio transport by default.
### Environment Variables
You can also set configuration via environment variables:
- `GA4_PROPERTY_ID`: Your Google Analytics 4 property ID
### Using with Claude Desktop
1. Install the server globally: `pip install mcp-server-ga4`
2. Set up your Google Cloud authentication: `gcloud auth application-default login`
3. Edit your Claude Desktop configuration:
```json
{
"mcpServers": {
"ga4": {
"command": "mcp-server-ga4",
"args": ["--property-id", "YOUR_GA4_PROPERTY_ID"]
}
}
}
```
## Available Tools
### run-report
Runs a standard GA4 report with configurable metrics, dimensions, and date ranges.
Parameters:
- `property_id` (optional): GA4 property ID (overrides the default)
- `metrics`: List of metric names (e.g., ["activeUsers", "sessions"])
- `dimensions` (optional): List of dimension names (e.g., ["date", "country"])
- `date_range`: Date range in one of these formats:
- `{"start_date": "YYYY-MM-DD", "end_date": "YYYY-MM-DD"}`
- `"last7days"`, `"last30days"`, `"today"`, `"yesterday"`
- `limit` (optional): Number of rows to return (default: 10)
### run-realtime-report
Gets real-time data for the past 30 minutes.
Parameters:
- `property_id` (optional): GA4 property ID (overrides the default)
- `metrics`: List of metric names (e.g., ["activeUsers", "screenPageViews"])
- `dimensions` (optional): List of dimension names (e.g., ["country", "city"])
- `limit` (optional): Number of rows to return (default: 10)
### get-metadata
Retrieves available metrics and dimensions for a GA4 property.
Parameters:
- `property_id` (optional): GA4 property ID (overrides the default)
- `type` (optional): Type of metadata to retrieve (`"metrics"`, `"dimensions"`, or `"all"`, default: `"all"`)
## Examples
### Running a standard report
```
What were the top 5 countries by active users in the last 30 days?
```
### Checking real-time data
```
How many users are currently active on the site?
```
### Getting metadata information
```
What metrics are available for me to query in GA4?
```
## Development
1. Clone the repository
2. Install development dependencies: `pip install -e ".[dev]"`
3. Run tests: `pytest`
## License
MIT
Connection Info
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