ga4-mcp-server
A Model Context Protocol server for Google Analytics 4 with both read and write access, enabling natural language reporting, configuration management, audience creation, and server-side event sending via Google credentials.
README
ga4-mcp-server
A Model Context Protocol (MCP) server for Google Analytics 4 with both read and write access. Connect it to Claude (or any MCP client) and pull reports, manage configuration, build remarketing audiences, and send server-side events — in natural language, using your own Google credentials. No third-party service, no subscription.
Most GA4 MCP servers are read-only. This one also writes: it can create custom dimensions and metrics, mark conversions, create audiences (for remarketing lists you can share to Google Ads), and manage/use the Measurement Protocol.
Features
Read
- List accounts and properties, property details, and data streams
- Run GA4 reports (
run_report) and realtime reports (run_realtime_report) - List custom dimensions, custom metrics, key events (conversions), and audiences
Write
- Create and archive custom dimensions
- Create custom metrics
- Create key events (conversions)
- Create and archive audiences (e.g. everyone who fired
generate_leadin the last 30 days) - Create / list / delete Measurement Protocol API secrets
- Send events into a property via the Measurement Protocol (with a
validate=Truemode that checks the payload without ingesting it)
Requirements
- Python 3.10+ (the MCP SDK requires it)
- A Google Cloud project and a service account with a JSON key
- The service account granted access on your GA4 account/property (Viewer/Analyst for reads, Editor for writes)
Google setup (one time)
- In the Google Cloud Console, create (or pick) a project.
- Enable the Google Analytics Data API and the Google Analytics Admin API for that project.
- Create a service account and download a JSON key for it.
- In Google Analytics → Admin → Account (or Property) access management, add the service account's email (
...@your-project.iam.gserviceaccount.com) as a user — Editor if you want write access.
That's it — no OAuth consent screen, no token refresh. The service account authenticates directly.
Install
Using uv (recommended — it manages an isolated Python for you):
git clone https://github.com/burhan29ee/ga4-mcp-server.git
cd ga4-mcp-server
uv venv --python 3.12 .venv
uv pip install --python .venv/bin/python -e .
Or with pip:
python3 -m venv .venv && source .venv/bin/activate
pip install -e .
Configure your MCP client
Point the server at your service-account key with the GOOGLE_APPLICATION_CREDENTIALS environment variable, then add it to your client. For Claude Desktop, edit claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/claude_desktop_config.json; Windows: %APPDATA%\Claude\claude_desktop_config.json):
{
"mcpServers": {
"ga4": {
"command": "/absolute/path/to/ga4-mcp-server/.venv/bin/python",
"args": ["-m", "ga4_mcp_server.server"],
"env": {
"GOOGLE_APPLICATION_CREDENTIALS": "/absolute/path/to/service-account-key.json"
}
}
}
}
Restart the client. You should be able to ask things like "list my GA4 properties," "pull last 28 days of users and conversions by channel," or "create a remarketing audience of everyone who registered for a webinar in the last 60 days."
Tool reference
| Tool | Type | What it does |
|---|---|---|
list_account_summaries |
read | List accounts and their properties |
get_property_details |
read | Property name, time zone, currency, industry |
list_data_streams |
read | Web/app streams and their measurement IDs |
run_report |
read | GA4 report by metrics/dimensions/date range |
run_realtime_report |
read | Realtime report (last ~30 min) |
list_custom_dimensions |
read | Custom dimensions on a property |
create_custom_dimension |
write | Create a custom dimension |
archive_custom_dimension |
write | Archive a custom dimension |
list_custom_metrics |
read | Custom metrics on a property |
create_custom_metric |
write | Create a custom metric |
list_key_events |
read | Key events (conversions) |
create_key_event |
write | Mark an event as a conversion |
list_audiences |
read | Audiences on a property |
create_event_audience |
write | Create an audience of users who fired an event |
archive_audience |
write | Archive an audience |
list_measurement_protocol_secrets |
read | MP API secrets for a stream |
create_measurement_protocol_secret |
write | Create an MP API secret |
delete_measurement_protocol_secret |
write | Delete an MP API secret |
send_ga4_event |
write | Send an event via the Measurement Protocol |
Development
pip install -e ".[dev]"
ruff check .
pytest -q
See CONTRIBUTING.md for the full workflow.
Security
The service-account key is a credential — treat it like a password. Never commit it (the .gitignore blocks key files), grant the service account the least access it needs, and rotate the key if it's ever exposed. See SECURITY.md for details and how to report a vulnerability.
Notes
- The
mcpdependency is pinned to>=1.2,<2. The 2.0 SDK reorganized its API and removedmcp.server.fastmcp, which this server uses. - Audiences use the GA4 Admin v1alpha API; the rest use the stable v1beta and Data APIs.
- This is an independent open-source project and is not affiliated with or endorsed by Google.
License
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.