google-analytics

Google Analytics 4

GA4 is event-based: every interaction is an event with parameters. Pick the reference from the decision tree below and read it before answering anything beyond the Quick Start.

The bundled analytics-mcp server (Google's official GA MCP) is read-only: it runs Data API reports, funnel and realtime reports, and reads account, property, custom-definition and Google Ads link details. Use it to answer questions about live GA4 data; configuration changes are made in the GA4 UI or through the Admin API outside this server.

Quick Start

1. Create property: analytics.google.com -> Admin -> Create -> Property
2. Create data stream: Add web stream, note Measurement ID (G-XXXXXXXXXX)
3. Install tracking (choose one):
   • GTM (recommended): Install container, create Google Tag with Measurement ID, trigger on All Pages, publish
   • gtag.js direct:

     <script async src="https://www.googletagmanager.com/gtag/js?id=G-XXXXXXXXXX"></script>
     <script>
       window.dataLayer = window.dataLayer || [];
       function gtag(){dataLayer.push(arguments);}
       gtag('js', new Date());
       gtag('config', 'G-XXXXXXXXXX');
     </script>
     

4. Verify: Enable GA Debugger extension, check Admin -> DebugView for session_start, page_view
5. Send custom events:

   gtag('event', 'button_click', { button_name: 'Subscribe', button_location: 'header' });
   

Decision Tree: Which Reference Do I Need?

What are you trying to do?

Setting up GA4 for the first time?         -> references/setup.md
Understanding how events work?              -> references/events-fundamentals.md
Implementing standard tracking events?      -> references/recommended-events.md
Creating business-specific custom events?   -> references/custom-events.md
Making parameters appear in reports?        -> references/custom-dimensions.md
Implementing User ID / cross-device?        -> references/user-tracking.md
Building audiences for remarketing?         -> references/audiences.md
Analysing data in GA4 reports?              -> references/reporting.md
Linking BigQuery / export schema?           -> references/bigquery.md
Querying export data with SQL?              -> the bigquery skill
Installing via gtag.js directly?            -> references/gtag.md
Setting up GA4 in Google Tag Manager?       -> references/gtm-integration.md
Sending events from server/backend?         -> references/measurement-protocol.md
Testing and debugging implementation?       -> references/debugview.md
Implementing GDPR/Consent Mode?             -> references/privacy.md
Configuring Admin settings?                 -> references/data-management.md

Core Concepts

Event-Based Model

GA4 tracks everything as events in four categories:

Category	Description	Examples
Automatic	Fire without configuration	session_start, first_visit
Enhanced Measurement	Toggle on/off in settings	scroll, click, file_download
Recommended	Google-defined with standard parameters	purchase, login, sign_up
Custom	Business-specific tracking	demo_requested, trial_started

Key Limits

Limit	Value
Distinct event names	500 per app stream (no limit for web)
Parameters per event	25
Event name length	40 characters
Parameter name/value length	40 / 100 characters (page_location 1,000)
Custom dimensions (event/user/item)	50 / 25 / 10
Audiences per property	100

Measurement ID

• Format: G-XXXXXXXXXX (G- prefix + 10 alphanumeric characters)
• Location: Admin -> Data Streams -> Web Stream
• Used in: gtag.js config, GTM tags, Measurement Protocol

Common Workflows

Ecommerce Tracking

1. Review recommended events for the purchase funnel: view_item -> add_to_cart -> begin_checkout -> purchase
2. Structure items array (required: item_id OR item_name; recommended: price, quantity, item_category)
3. Test with DebugView, then register custom item parameters as custom dimensions

Cross-Device Tracking

1. Implement User ID and configure Reporting Identity (Admin -> Data Settings)
2. Set user properties and build cross-device audiences

GDPR Compliance

1. Set up Consent Mode with default denied state
2. Integrate with CMP (OneTrust, Cookiebot, etc.), update consent on user acceptance
3. Test consent implementation with DebugView

Custom Reports

1. Understand available data in reporting
2. Register custom parameters as dimensions, create Explorations
3. For unsampled data, export to BigQuery

Best Practices

• Naming: Use snake_case, be descriptive and action-oriented, keep under 40 characters, avoid generic names
• Implementation order: Enhanced Measurement -> recommended events -> custom events -> custom dimensions
• Data quality: Separate test/production properties, set up internal traffic filters from day one, document all custom events, audit regularly with DebugView, export to BigQuery for backup