google-analytics-mcp-server
Provides read-only access to Google Analytics 4 properties, enabling reporting, pivot tables, funnels, realtime data, and inspection of property configuration such as data streams, custom definitions, key events, and audiences.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@google-analytics-mcp-serverShow me top pages by users over the last 7 days."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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-serverPrefer 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
27 read tools | Reports, pivots, funnels, realtime, plus the Admin API: properties, data streams, custom definitions, key events, audiences |
Diagnostics | Ecommerce, BigQuery export, server-side tagging, audience exports, quota snapshots |
51 metrics, 62 dimensions | With a compatibility matrix that catches invalid combinations before they hit the API |
6 resources | Live catalogues the model can read: metrics, dimensions, compatibility rules, 12 workflow recipes |
Identifier redaction | User, email and device identifiers redacted by default on access bindings and audience exports, with explicit opt-in to see them |
No writes at all | Not a flag, a property of the code. See below |
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.
Related MCP server: Delmain GA4 MCP
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.
Google's official server | This server | ||
Tools | 7 | 27 | 27, plus 5 other platforms |
Hosting | Local, via pipx | Local, via npx | Hosted for you |
Read-only | ✅ | ✅ | ✅ |
Reports |
| Same, plus pivots, batch reports, advanced funnels | Same |
Admin API | Account summaries, property details, custom definitions | Broader: data streams, key events, channel groups, audiences, audience exports | Same |
Diagnostics | ❌ | Ecommerce, BigQuery export, server-side tagging, quotas | Same |
Metric compatibility | None | Catalogue and matrix, checkable before the call | Same |
Identifier redaction | ❌ | Default on, opt-in to disable | Same |
Language | Python | TypeScript | |
Status | Labelled experimental by Google | 1.0 |
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.
Tool | Behaviour |
| Access bindings have user and email identifiers redacted |
| Identifier columns redacted, matched against the export's own dimension metadata |
| Same redaction on the row sample |
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-serverCursor
.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 startConfiguration
Variable | Default | Meaning |
| none | Required. OAuth client ID |
| none | Required. OAuth client secret |
| none | Required. From the consent flow |
| none | Optional default, saves passing it on every call |
|
|
|
Check your setup at any time:
npm run doctorTools
Discovery and health
Tool | Purpose |
| Validates credentials and lists reachable properties |
| Accounts and properties you can reach |
| Timezone, currency, industry, data retention |
| Metrics and dimensions available on a given property |
Reporting
Tool | Purpose |
| The main reporting tool. Named metrics and dimensions |
| Pivot tables |
| Several reports in one call |
| The last 30 minutes |
| Funnel analysis with step conditions |
| Prebuilt funnels for common journeys |
| Check a combination before running it |
Configuration
Tool | Purpose |
| Data streams, users, links. Access-binding identifiers redacted |
| Custom dimensions and metrics |
| Key events and their counting method |
| Default and custom channel groupings |
| Parameters actually collected on an event |
Audiences
Tool | Purpose |
| Audience definitions and their health |
| Audience exports and their rows |
| Why an export is empty or stale |
Diagnostics
Tool | Purpose |
| Whether ecommerce events are complete and coherent |
| BigQuery export configuration and freshness |
| Server-side tagging signals |
| Remaining Data API quota tokens |
URI | Contents |
| What this server exposes, and which tool to run first |
| All 51 metrics with categories and formats |
| All 62 dimensions and where they are valid |
| The compatibility matrix |
| 12 step-by-step workflows |
| Diagnostic playbooks |
Security
The client secret and refresh token are never logged, at any log level, or written to disk.
Three hosts are contacted, and only three:
analyticsdata.googleapis.com,analyticsadmin.googleapis.comandoauth2.googleapis.com. A test fails the build if a fourth host appears in the source.No fetch follows a redirect. Every outbound call sets
redirect: "error", so a redirect cannot forward a bearer token or client secret to another host. A test fails the build if any fetch omits this.No telemetry. The server makes no network call other than to Google.
Full policy, including how personal data is handled: SECURITY.md.
Looking for a managed, multi-platform version?
This server does one platform, on your machine, with your credentials. That is on purpose.
If you'd rather not run it yourself, or you need Google Analytics alongside Meta Ads, Google Ads, TikTok Ads, Pinterest Ads and Search Console behind one endpoint, with hosted OAuth and cross-platform reporting, that's what we build at getmcpads.com.
Same philosophy, less plumbing. This project stays open source and independently useful either way.
Contributing
Issues and pull requests are welcome. See CONTRIBUTING.md. Please read SECURITY.md before reporting anything security-related.
Licence
Apache License 2.0. See also NOTICE.
Google, Google Analytics and GA4 are trademarks of Google LLC. This project is not affiliated with, endorsed by, or sponsored by Google LLC. It is an independent client of a public API.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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- AlicenseAqualityBmaintenanceEnables querying Google Analytics 4 properties using natural language through MCP clients. Supports customizable reports with any dimensions and metrics, listing properties, and real-time data.4MIT
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