paolobietolini/gtm-mcp-server: An MCP server for Google Tag Manager. Connect it to your LLM, authenticate once, and start managing GTM through natural language.

Let AI manage your Google Tag Manager containers.

Create tags, audit configurations, generate tracking plans, and publish changes, all through natural conversation with Claude or ChatGPT.

URL: https://mcp.gtmeditor.com

Ask your AI assistant to:

• “List all my GTM containers”
• “Create a GA4 event tag for form submissions”
• “Audit this container for issues and duplicates”
• “Generate a tracking plan document for the marketing team”
• “Set up ecommerce tracking for purchases”
• “Publish the changes we just made”

No more clicking through the GTM interface. No more copy-pasting configurations. Just describe what you need.

Claude.ai:

1. Go to Settings → Connectors → Add Custom Connector
2. Enter: https://mcp.gtmeditor.com
3. Click Add and sign in with Google

Claude Code (CLI):

claude mcp add -t http gtm https://mcp.gtmeditor.com

1. Go to OpenAI Apps Platform
2. Add an MCP integration with URL: https://mcp.gtmeditor.com
3. Authorize with your Google account

Create and modify any GTM tag type:

• GA4 Configuration & Events — Set up Google Analytics 4 with proper measurement IDs
• Ecommerce Tracking — Purchase, add-to-cart, view-item events
• Custom HTML — Inject scripts, pixels, and custom code
• Custom Image — Tracking pixels with cache busting

Build triggers for any scenario:

• Page views (all pages or specific URLs)
• Custom dataLayer events
• Click tracking
• Form submissions
• Timer-based triggers
• Trigger groups for complex conditions

• Browse accounts, containers, and workspaces
• Create versions from workspace changes
• Publish versions to go live
• Organize with folders
• Enable/disable built-in variables

Full support for server-side GTM containers:

• Clients — Create, update, and delete server-side clients (e.g. GA4 client)
• Transformations — Control event parameters with allow, exclude, and augment rules

Import templates from Google’s Community Template Gallery:

• “Import the iubenda cookie consent template”
• “Add Cookiebot to my container”
• “Set up Facebook Pixel using the gallery template”

The AI will search for the template, find the GitHub repository, and import it automatically.

Container Audit
“Audit my container for issues” — Analyzes your workspace for:

• Naming inconsistencies
• Duplicate tags
• Orphaned triggers
• Security concerns
• Best practice violations

Tracking Plan Generation
“Generate a tracking plan” — Creates markdown documentation of:

• All events and their triggers
• Data layer requirements
• Variable definitions
• Implementation notes

GA4 Setup Recommendations
“Help me set up GA4 for ecommerce” — Recommends:

• Which tags to create
• Trigger configurations
• Required variables
• Data layer implementation code

Ask AI to create a full GA4 ecommerce implementation from scratch:

• “Set up GA4 ecommerce tracking for my store”
• Creates 12+ tags (configuration + all ecommerce events)
• Creates matching triggers for each dataLayer event
• Creates data layer variables for items, currency, value, transaction_id
• Follows Google’s recommended event naming and parameters

Integrate privacy tools like OneTrust with your tracking:

• “Make GA4 fire only when analytics consent is granted”
• Creates consent-checking variables
• Sets up conditional triggers
• Updates existing tags to respect user choices

Manage containers at scale:

• “Add ‘ecom -‘ prefix to all ecommerce triggers”
• “Update all tags to use a measurement ID variable”
• Rename, update, or organize dozens of items through conversation

Create sophisticated tracking logic:

• “Create a variable that returns the local timestamp”
• “Add a custom parameter to the purchase tag”
• Custom JavaScript variables, data layer mappings, and more

• Manage multiple client containers (7+ accounts shown in demo)
• Standardize implementations across clients
• Rapid setup for new projects
• Version and publish changes safely

The GTM MCP Server connects AI assistants to the Google Tag Manager API using the Model Context Protocol. When you ask Claude or ChatGPT to manage your GTM, it:

1. Authenticates with your Google account (OAuth 2.1)
2. Reads your container configurations
3. Executes the changes you request
4. Confirms before destructive operations

Your credentials are never stored—the server uses token-based authentication that you can revoke anytime from your Google account.

• Confirmation required for deletions and publishing
• Workspace-only changes — nothing goes live until you publish
• Version control — all changes create a version first
• Audit logging — track what was changed

Want to run your own instance?

git clone https://github.com/paolobietolini/gtm-mcp-server.git
cd gtm-mcp-server

# Create .env file
cat > .env  'EOF'
GOOGLE_CLIENT_ID=your-client-id.apps.googleusercontent.com
GOOGLE_CLIENT_SECRET=your-client-secret
JWT_SECRET=$(openssl rand -base64 32)
BASE_URL=http://localhost:8080
EOF

# Start the server
docker compose up -d

# Add to Claude
claude mcp add -t http gtm http://localhost:8080

1. Go to Google Cloud Console
2. Enable the Tag Manager API
3. Create OAuth 2.0 credentials (Web application)
4. Add redirect URIs:

   https://claude.ai/api/mcp/auth_callback
   https://claude.com/api/mcp/auth_callback
   https://chatgpt.com/connector_platform_oauth_redirect
   https://your-domain.com/oauth/callback
   

Access GTM data via structured URIs:

gtm://accounts
gtm://accounts/{id}/containers
gtm://accounts/{id}/containers/{id}/workspaces
gtm://accounts/.../workspaces/{id}/tags
gtm://accounts/.../workspaces/{id}/triggers
gtm://accounts/.../workspaces/{id}/variables

For best results, install the GTM API skill so your AI assistant understands GTM’s API structure, parameter formats, and validation rules.

# One-liner install
curl -sL https://github.com/paolobietolini/gtm-api-for-llms/archive/main.tar.gz | tar xz && \
  mkdir -p ~/.claude/skills && \
  cp -r gtm-api-for-llms-main/skills/gtm-api ~/.claude/skills/ && \
  rm -rf gtm-api-for-llms-main

Or clone and copy:

git clone https://github.com/paolobietolini/gtm-api-for-llms.git
cp -r gtm-api-for-llms/skills/gtm-api ~/.claude/skills/

curl -sL https://github.com/paolobietolini/gtm-api-for-llms/archive/main.tar.gz | tar xz && \
  mkdir -p ~/.codex/skills && \
  cp -r gtm-api-for-llms-main/skills/gtm-api ~/.codex/skills/ && \
  rm -rf gtm-api-for-llms-main

The GTM API for LLMs repository provides LLM-optimized documentation: request templates, validation rules, workflow algorithms, and complete schemas for all GTM entity types including server-side containers.

• Protocol: Model Context Protocol (MCP) over HTTP
• Authentication: OAuth 2.1 with PKCE
• Standards: RFC 8414, RFC 7591, RFC 9728

When creating or updating linkClick, click, or formSubmission triggers via the API, the autoEventFilter field (used for “Some Link Clicks”https://github.com/”Some Form Submissions” conditions) is silently dropped by the Google Tag Manager API. The API returns 200 OK with a new fingerprint but does not persist the autoEventFilter.

This has been confirmed by HTTP-level debugging: the correct JSON is sent in the request body, but Google’s response omits the field. The filter and customEventFilter fields work correctly.

Workaround: Configure autoEventFilter conditions manually through the GTM web interface. The MCP server can read triggers that have autoEventFilter set via the UI.

Status: #33

Paolo Bietolini

mcp@paolobietolini.com

BSD-3-Clause