mcp-server-ga4

# 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