google-analytics-mcp-server

An open-source Model Context Protocol server for Google Analytics 4. It lets Claude, ChatGPT, Cursor or any MCP client query your analytics data and inspect how your property is configured.

Read-only, with no way to turn that off. You run it, and your credentials stay on your machine.

npx -y @getmcpads/google-analytics-mcp-server

Also listed in the MCP Registry as com.getmcpads/google-analytics, so clients that read the registry can install it by name.

Prefer not to run it yourself? getmcpads.com is the hosted version of this server, with Google Analytics alongside Meta Ads, Google Ads, TikTok Ads, Pinterest Ads and Search Console behind a single endpoint, hosted OAuth, and cross-platform reporting. Same tools, same safety model, no setup.

What you get

Compatibility, checked before the call

GA4 rejects many metric and dimension combinations, and its errors rarely explain which pair is at fault. This server carries the compatibility matrix, so ga4_check_compatibility and ga4_validate_query let the model verify a combination before spending a call and a quota token on it.

Quotas matter here more than on ad platforms: GA4 charges tokens per property per day, and a few careless exploratory queries can exhaust them. ga4_get_property_quotas_snapshot shows what is left.

How this compares to Google's own MCP server

The Google Analytics team ships an official MCP server, and it is good. It is Apache-2.0, runs locally, is read-only, and has a large community. Be clear about what differs.

Neither is more private than the other. Both run locally and read only. If the seven official tools cover what you need, and your model writes clean GA4 report requests, use Google's: it is maintained by the team that owns the API.

Choose this one when you want named metrics validated against a compatibility matrix rather than raw request bodies, when you need the configuration and diagnostics surface, or when you want identifiers redacted by default rather than by discipline. Choose getmcpads.com if you want this server's capabilities without running it, or you need analytics and ad platforms in the same conversation.

Read-only, and why it stays that way

There are no write tools, and no environment variable that adds any. Every tool calls a read method of the Data API or the Admin API.

This is not caution for its own sake. A misread report is a wrong answer you can spot. A mistaken write to an analytics property, a deleted audience or an edited data stream, corrupts the record you use to judge everything else, and often silently. The other servers we publish do have write tools, guarded by a mandatory preview. This one has none.

Our ad platform servers with guarded writes: Meta Ads · Google Ads · TikTok Ads

Personal data

Analytics data is not anonymous by default. A GA4 property can carry a userId you set yourself, a device identifier, or a Google Signals pseudonymous ID. An MCP conversation sends whatever a tool returns to a model.

Identifiers are redacted by default wherever this server can return them, and showing them is an explicit opt-in, never the default.

Every one of these accepts includePersonalIdentifiers: true to return raw values, and defaults to false.

Audience export rows are positional, so the redaction reads the export's dimension metadata to find identifier columns. If that metadata is missing, every value in the row is redacted rather than guessing which column is safe. Failing closed is the point.

Report rows are not redacted. ga4_run_report and the other reporting tools return what you asked for. Altering the numbers a report returns would be worse than returning them.

So one decision stays yours: if your property carries a userId you consider personal, do not request it as a report dimension in a conversation whose transcript leaves your machine.

Getting credentials

Three values, obtained once.

1. OAuth client

In a Google Cloud project, enable the Google Analytics Data API and the Google Analytics Admin API, then create an OAuth client under APIs & Services → Credentials. Choose Desktop app for local use. Note the client ID and client secret.

2. Refresh token

Run the OAuth consent flow once, signed in as a Google account with access to your GA4 properties, and keep the refresh token. The analytics.readonly scope is enough, and it is the only one you should grant.

📖 Google OAuth for installed apps

The refresh token does not expire. It is the sensitive value: anyone holding it can mint access tokens indefinitely. Use an OAuth client dedicated to this server so you can revoke it on its own.

3. Property ID, optional

Set GA4_PROPERTY_ID to avoid passing it on every call. Find it in GA4 under Admin → Property Settings, or list them with ga4_list_properties.

Run ga4_health_check as your first call. It verifies the credentials and lists the properties you can actually reach, without printing any secret.

Setup

Claude Desktop

~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "google-analytics": {
      "command": "npx",
      "args": ["-y", "@getmcpads/google-analytics-mcp-server"],
      "env": {
        "GA4_CLIENT_ID": "your-client-id",
        "GA4_CLIENT_SECRET": "your-client-secret",
        "GA4_REFRESH_TOKEN": "your-refresh-token"
      }
    }
  }
}

Restart Claude Desktop. Ask it: "list my Google Analytics properties".

Claude Code

claude mcp add google-analytics --env GA4_CLIENT_ID=... --env GA4_CLIENT_SECRET=... --env GA4_REFRESH_TOKEN=... -- npx -y @getmcpads/google-analytics-mcp-server

Cursor

.cursor/mcp.json in your project, same shape as the Claude Desktop config above.

From source

git clone https://github.com/getmcpads-com/google-analytics-mcp-server.git
cd google-analytics-mcp-server
npm install && npm run build
cp .env.example .env   # then fill in your credentials
npm start

Configuration

Check your setup at any time:

npm run doctor

Tools