Google Analytics 4 MCP

Name: Google Analytics 4 MCP
Author: scalably-io

by scalably-ioversion 1.0.1i★ –iRuns on your computer

Registry nameio.scalably/ga4-mcp

Install

Overview

Description from the maker (original English)

Google Analytics 4 MCP: reports, realtime, funnels, pivots, metadata, admin lists. 17 tools.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Marketing & social media
You need to fill in: GOOGLE_APPLICATION_CREDENTIALS

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: GOOGLE_APPLICATION_CREDENTIALS, GA4_LOG_LEVEL

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Download the maker’s .mcpb file

The link goes to the maker’s own file; we do not host or repackage it. Open the file and Claude Desktop installs it.

Run this in your terminal

claude mcp add ga4 --env GOOGLE_APPLICATION_CREDENTIALS=your-value --env GA4_LOG_LEVEL=your-value -- uvx scalably-ga4-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "ga4": {
      "command": "uvx",
      "args": [
        "scalably-ga4-mcp"
      ],
      "env": {
        "GOOGLE_APPLICATION_CREDENTIALS": "your-value",
        "GA4_LOG_LEVEL": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "ga4": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "scalably-ga4-mcp"
      ],
      "env": {
        "GOOGLE_APPLICATION_CREDENTIALS": "your-value",
        "GA4_LOG_LEVEL": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

GOOGLE_APPLICATION_CREDENTIALS required env
Path to a Google service-account JSON file with the analytics.readonly scope; add the service account as a Viewer on each GA4 property
GA4_LOG_LEVEL env
Log level, default INFO

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

✓ Pass
Maker matches the repo
The registry name was verified against the domain scalably.io (the registry checks domain ownership)
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Marketing & social mediai

More stars than 0% of the other 3581 servers in this category
Published to the registry more recently than 32% of the other 3581 servers in this category
Basic checks equal to or better than 100% of the other 3581 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Google Analytics 4 MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: GOOGLE_APPLICATION_CREDENTIALS

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.1) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv), MCPB on your computer.

What can I use instead?

In the same category: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Google Analytics 4 MCP

Read-only MCP server for Google Analytics 4. Seventeen tools cover the read surface of both the Data API and the Admin API: standard, batch, pivot, realtime and funnel reports; the metadata catalog and compatibility check; and admin lists for properties, streams, custom dimensions and metrics, key events, audiences, Google Ads links, annotations and access reports. We run this server in production for every analytics client.

Install

Claude Code:

claude mcp add ga4 -e GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account.json -- uvx scalably-ga4-mcp

Codex:

codex mcp add ga4 --env GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account.json -- uvx scalably-ga4-mcp

Claude Desktop: download ga4-mcp.mcpb from the latest GitHub release and open it.

Setup

In Google Cloud, create or pick a project and enable the Google Analytics Data API and the Google Analytics Admin API on it (APIs and Services, Library).
Create a service account in that project and download its JSON key.
Add the service account's email as a Viewer on each GA4 property you want to query (Admin, Property access management).

No OAuth consent screen is needed; the server authenticates as the service account with the analytics.readonly scope. One service account can read any property that grants it access, so there is no per-client configuration beyond step 3 above.

Call ga4_list_account_summaries first to discover which property_id values the service account can see, then pass one into the reporting or admin tools.

Tools (17)

Tool	What it does
`ga4_list_account_summaries`	List every GA4 account and its child properties accessible to this service account
`ga4_get_property_details`	Full metadata for a single GA4 property
`ga4_list_data_streams`	List all data streams (web, iOS, Android) on a GA4 property
`ga4_list_custom_dimensions`	List custom dimensions configured on a GA4 property
`ga4_list_custom_metrics`	List custom metrics configured on a GA4 property
`ga4_list_key_events`	List key events (formerly conversions) on a GA4 property
`ga4_list_audiences`	List audiences defined on a GA4 property
`ga4_list_google_ads_links`	List Google Ads links attached to a GA4 property
`ga4_list_property_annotations`	List reporting annotations on a GA4 property
`ga4_run_access_report`	Audit log of who read what on a GA4 property, last 12 months
`ga4_get_metadata`	Fetch the full GA4 dimension and metric catalog for a property
`ga4_run_report`	Run a GA4 standard report, the workhorse tool
`ga4_batch_run_reports`	Run up to 5 GA4 reports in a single round trip
`ga4_run_pivot_report`	Run a GA4 pivot report
`ga4_run_realtime_report`	Run a GA4 real-time report covering the last 30 minutes
`ga4_check_compatibility`	Validate whether a dimension and metric combo can be queried together
`ga4_run_funnel_report`	Run a GA4 funnel report (v1alpha, drop-off analysis)

Configuration

Variable	Required	Purpose
`GOOGLE_APPLICATION_CREDENTIALS`	yes	Path to a Google service-account JSON file with the `analytics.readonly` scope; share each property with the service account email
`GA4_LOG_LEVEL`	no	INFO (default) or DEBUG

Filter expression shape

Every tool accepting dimension_filter / metric_filter takes a dict:

{"filter": {"field_name": "country", "string_filter": {"value": "US"}}}

Compose with boolean groups:

{"and_group": {"expressions": [

{"filter": {"field_name": "country", "string_filter": {"value": "US"}}}, {"filter": {"field_name": "deviceCategory", "string_filter": {"value": "mobile"}}} ]}}

A raw {"field_name": ..., "string_filter": ...} is auto-wrapped into {"filter": {...}}.

Reply shape

Every tool returns JSON with status (succeeded, partial, no_op), operation, summary, target, result, proof, warnings, recovery. Failures surface as a tool error whose text is ga4_request_failed: . proof.nextOffset on a partial status means: continue from that offset. proof.propertyQuota carries the property's remaining Data API quota so the caller can self-throttle. proof.dataQualityLimited is true when the response was sampled, thresholded, or collapsed high-cardinality rows into (other); treat such a result as directionally useful, not exact.

Limits

250,000 rows per Data API response (the server caps any higher client-supplied limit). Batch reports: up to 5 per call. Funnel reports: up to 10 steps. Realtime reports use a separate, smaller dimension and metric catalog covering only the last 30 minutes; non-realtime data typically lags 24 to 48 hours. Funnel reporting is v1alpha and its shape can change upstream. Every quota bucket (core reports, realtime, funnel) allows roughly 14,000 quota tokens per project per property per hour (a complex query can cost more than one token); 360 properties get a 10x multiplier. Re-check Google's current quota page before relying on an exact number.

Verify

Each release lists the package version, the .mcpb sha256 and the production commit it was derived from in CHANGELOG.md. CI runs the tests and a clean install of the built wheel on every push.

Privacy Policy

This server runs locally, on your machine, under your own credentials. It collects no personal data, contains no telemetry, stores nothing persistently, and talks only to the vendor API it wraps. No third party, including Scalably, receives your data. Contact: hello@scalably.io. Canonical copy: https://scalably.io/connector-privacy.html

Google Analytics 4 MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Marketing & social mediai

Common questions

Alternatives

MCP YouTube Transcript

Google Analytics MCP

BibiGPT YouTube Video Summarizer

README from the maker

Google Analytics 4 MCP

Install

Setup

Tools (17)

Configuration

Filter expression shape

Reply shape

Limits

Verify

Privacy Policy

License