Google Tag Manager
Integrates Google Tag Manager to automate GTM configuration and component creation through natural language prompts.
Google Tag Manager MCP Server
A Model Context Protocol (MCP) server that integrates Google Tag Manager with Claude, enabling automated GTM configuration and component creation through natural language prompts.
Features
- GTM API Integration: Full Google Tag Manager API integration for creating and managing tags, triggers, and variables
- Component Templates: Pre-built templates for common tracking scenarios (GA4, Facebook Pixel, conversion tracking)
- Workflow Automation: Complete workflow creation for different site types (ecommerce, lead generation, content sites)
- Claude Integration: Natural language interface for GTM configuration through Claude
Setup
1. Install Dependencies
Option A: Using uv (Recommended)
# Install uv if not already installed
curl -LsSf https://astral.sh/uv/install.sh | sh
source $HOME/.local/bin/env
# Install dependencies
uv sync
Option B: Using pip
pip install -r requirements.txt
2. Google Cloud Console Setup
- Go to the Google Cloud Console
- Create a new project or select existing one
- Enable the Tag Manager API:
- Go to "APIs & Services" > "Library"
- Search for "Tag Manager API"
- Click "Enable"
3. Create Service Account Credentials
- Go to "APIs & Services" > "Credentials"
- Click "Create Credentials" > "OAuth 2.0 Client IDs"
- Choose "Desktop application"
- Download the JSON file and save it as
credentials.jsonin this directory
4. Configure Claude
Add the MCP server configuration to your Claude config:
{
"mcpServers": {
"gtm": {
"command": "python",
"args": ["/path/to/mcp-for-gtm/server.py"],
"env": {
"GTM_CREDENTIALS_FILE": "/path/to/mcp-for-gtm/credentials.json",
"GTM_TOKEN_FILE": "/path/to/mcp-for-gtm/token.json"
}
}
}
}
Available Tools
Basic GTM Operations
create_gtm_tag: Create individual GTM tagscreate_gtm_trigger: Create GTM triggerscreate_gtm_variable: Create GTM variableslist_gtm_containers: List all containers for an accountget_gtm_container: Get container detailspublish_gtm_version: Publish a container version
Workflow Tools
create_ga4_setup: Complete Google Analytics 4 setup with config tag and common eventscreate_facebook_pixel_setup: Facebook Pixel tracking setupcreate_form_tracking: Form submission tracking setupgenerate_gtm_workflow: Generate complete workflows for different site types
Usage Examples
1. Set up Google Analytics 4 tracking
Create a complete GA4 setup for my website with measurement ID G-XXXXXXXXXX in GTM account 123456 and container 7890123
2. Generate ecommerce tracking workflow
Generate a complete ecommerce tracking workflow with GA4 measurement ID G-XXXXXXXXXX and Facebook Pixel ID 123456789
3. Create form tracking
Set up form tracking for the contact form with selector #contact-form in my GTM container
4. Create custom components
Create a custom GTM tag for tracking video plays with the following parameters: event_name = "video_play", video_title = "{{Video Title}}", video_duration = "{{Video Duration}}"
Workflow Types
The generate_gtm_workflow tool supports three main workflow types:
ecommerce: Enhanced ecommerce tracking with purchase, cart, and product interaction eventslead_generation: Form submissions, CTA clicks, and conversion trackingcontent_site: Content engagement, newsletter signups, and social sharing
Authentication
On first run, the server will open a browser window for OAuth authentication. Grant the necessary permissions to access your GTM account. The authentication token will be saved for future use.
File Structure
mcp-for-gtm/
├── server.py # Main MCP server
├── gtm_client.py # GTM API client
├── gtm_components.py # Component templates and workflow builder
├── requirements.txt # Python dependencies
├── config.json # MCP server configuration
├── credentials.json # Google OAuth credentials (you provide)
├── token.json # Generated auth token (auto-created)
└── README.md # This file
Troubleshooting
Authentication Issues
- Ensure
credentials.jsonis properly configured from Google Cloud Console - Check that Tag Manager API is enabled in your Google Cloud project
- Verify you have the necessary permissions in your GTM account
Permission Errors
- Make sure your Google account has edit permissions for the GTM container
- Ensure the GTM account and container IDs are correct
API Errors
- Check your GTM account and container IDs
- Verify that the workspace exists (default workspace ID is used)
- Check rate limits if you're making many requests
Development
Running Tests
# Using uv
uv run python test_server.py
# Or directly with python
python test_server.py
Running the Server
# Using the convenience script
./run_server.sh
# Or manually with uv
uv run python server.py
# Or with system python
python server.py
Development Dependencies
The project includes development dependencies for code quality:
# Format code with black
uv run black .
# Check with flake8
uv run flake8 .
# Type checking with mypy
uv run mypy .
# Run tests with pytest
uv run pytest
Contributing
Feel free to submit issues and enhancement requests!
관련 서버
Alpha Vantage MCP Server
스폰서Access financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
Exploit Intelligence Platform MCP Server
An MCP (Model Context Protocol) server that gives AI assistants access to the Exploit Intelligence Platform — hundreds of thousands of vulnerabilities and exploits from NVD, CISA KEV, VulnCheck KEV, InTheWild.io, ENISA EUVD, OSV.dev, EPSS, ExploitDB, Metasploit, GitHub, and more. I
Ansible & OpenShift Automation
Provides tools to interact with the Ansible Automation Platform API for automation tasks.
Mermaid
Generate mermaid diagram and chart with AI MCP dynamically.
FastAPI MCP Server
A MCP server implementation using the FastAPI framework, configurable via environment variables.
Autodocument
Automatically generates documentation for code repositories by analyzing directory structures and code files using the OpenRouter API.
Argo CD
Interact with Argo CD applications through natural language.
Comet Opik
Query and analyze your Opik logs, traces, prompts and all other telemtry data from your LLMs in natural language.
Dappier MCP Server
An MCP server for interacting with Dappier's Retrieval-Augmented Generation (RAG) models.
Adobe After Effects
Control Adobe After Effects through a standardized protocol, enabling AI assistants and other applications.
MCP Client for Ollama
A Python client that connects local LLMs via Ollama to Model Context Protocol servers, enabling them to use tools.