Google Analytics MCP

Name: Google Analytics MCP
Author: surendranb

by surendranbversion 2.11.7i★ 244iRuns on your computer

Registry nameio.github.surendranb/google-analytics-mcp

Overview

Description from the maker (original English)

GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.

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 checksi3 of 3 passedChecked from public information; code not scanned yet
UsageiEarly★ 244

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, GA4_PROPERTY_ID

Install

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

You need

PyPIPython’s uv installed (for the uvx command)

Claude DesktopClaude CodeCursorVS Code

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "google-analytics": {
      "command": "uvx",
      "args": [
        "google-analytics-mcp"
      ],
      "env": {
        "GOOGLE_APPLICATION_CREDENTIALS": "your-value",
        "GA4_PROPERTY_ID": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add google-analytics --env GOOGLE_APPLICATION_CREDENTIALS=your-value --env GA4_PROPERTY_ID=your-value -- uvx google-analytics-mcp

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

{
  "mcpServers": {
    "google-analytics": {
      "command": "uvx",
      "args": [
        "google-analytics-mcp"
      ],
      "env": {
        "GOOGLE_APPLICATION_CREDENTIALS": "your-value",
        "GA4_PROPERTY_ID": "your-value"
      }
    }
  }
}

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "google-analytics": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "google-analytics-mcp"
      ],
      "env": {
        "GOOGLE_APPLICATION_CREDENTIALS": "your-value",
        "GA4_PROPERTY_ID": "your-value"
      }
    }
  }
}

Values you fill in

GOOGLE_APPLICATION_CREDENTIALS secret required env
Absolute path to your Google Cloud service account JSON key with GA4 property access.
GA4_PROPERTY_ID required env
Numeric GA4 Property ID to query, for example 123456789.

Values marked secret are keys to your account. Never share them or paste them into a chat.

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

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 5, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account surendranb, which owns the repo
✓ Pass
Still maintained
Code last changed 3 days ago
✓ Pass
Has a licence
Uses MIT
– 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
Needs the server’s tool list first; this check starts in the next step

Compared with others in Marketing & social mediai

More stars than 83% of the other 6 servers in this category
Published to the registry more recently than 83% of the other 6 servers in this category
Basic checks equal to or better than 100% of the other 6 servers in this category

Compared only with servers in this prototype, not the whole registry.

Common questions

Is Google Analytics MCP safe?

It passed 3 of 3 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, GA4_PROPERTY_ID

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 3 days ago, and the latest version (2.11.7) reached the registry 8 days 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) on your computer.

What can I use instead?

In the same category: MCP YouTube Transcript, BibiGPT YouTube Video Summarizer, gtm-api: LinkedIn MCP Server

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

MCP YouTube Transcript

by jkawamoto

An MCP server retrieving transcripts of YouTube videos

Runs on your computer★ 495MITUpdated 8 days ago

BibiGPT YouTube Video Summarizer

by JimmyLv

AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.

Runs in the cloud★ 137MITUpdated 8 days ago

gtm-api: LinkedIn MCP Server

by gtm-api

Managed LinkedIn MCP server for AI agents: search, connect, message and enrich on accounts you own.

Computer or cloud★ 90MITUpdated 2 days ago

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 (GA4) MCP Server 📊

Model Context Protocol (MCP) server for Google Analytics 4: real-time query exploration, schema discovery, metric aggregation, and audience insights for AI agents.

🌐 Live Documentation & Web Portal: https://ga4mcp.com/

⚡ Quickstart

# 1-Line Universal Installer (Auto-configures Claude Desktop, Cursor, Claude Code, Antigravity, VS Code, Zed, Windsurf)

curl -fsSL "https://ga4.builditwithai.xyz/install" | bash

Or run directly via your preferred runtime:

uvx google-analytics-mcp uvx --from google-analytics-mcp ga4-mcp-server python -m ga4_mcp npx -y @surendranb/google-analytics-mcp

🤖 Client Setup

A. Claude Code (CLI)

claude mcp add google-analytics -- uvx google-analytics-mcp

B. Cursor & Google Antigravity (`mcp.json`)

"mcpServers": { "google-analytics": { "command": "uvx", "args": ["google-analytics-mcp"] } } }

C. Claude Desktop (`claude_desktop_config.json`)

"mcpServers": { "google-analytics": { "command": "uvx", "args": ["google-analytics-mcp"], "env": { "GA4_PROPERTY_ID": "your_ga4_property_id", "GOOGLE_APPLICATION_CREDENTIALS": "/path/to/service_account.json" } } } }

D. VS Code (Cline / Roo Code / Continue)

"mcpServers": { "google-analytics": { "command": "npx", "args": ["-y", "@surendranb/google-analytics-mcp"] } } }

🛠️ Tools & Capabilities

Tool Name	Parameters	Description	Return Type
`get_ga4_data`	`dimensions` (list), `metrics` (list), `date_ranges` (list), `limit` (int)	Runs multi-dimensional GA4 reports with automated metric totals and server-side aggregation.	`JSON / Markdown`
`list_accounts`	(none)	Lists all accessible Google Analytics accounts and permission levels.	`JSON`
`list_properties`	`account_id` (optional)	Lists all GA4 properties associated with an account.	`JSON`
`get_property_metadata`	`property_id` (optional)	Fetches complete dimension and metric schemas, custom definitions, and compatibility rules.	`JSON`
`run_realtime_report`	`metrics` (list), `dimensions` (list)	Queries real-time active users and event counts from the last 30 minutes.	`JSON`
`search_skills`	`query` (string)	Searches built-in GA4 analytical playbooks (e-commerce, channel attribution, bot filtering).	`Markdown`
`skill_read`	`skill_name` (string)	Dynamically loads procedural skills and analytical guides from GitHub.	`Markdown`
`skills_list`	(none)	Lists all available live GA4 analytical skills.	`JSON`

🧠 Dynamic Skills & Guided Playbooks

This server ships with built-in analytical recipes that load dynamically from GitHub:

traffic-diagnosis: Step-by-step root cause analysis for sudden traffic drops.
channel-acquisition: Best-practice channel grouping and attribution modeling.
ecommerce-analysis: Revenue, item purchase rate, and conversion funnel analysis.
ai-referral-analysis: Tracks and isolates referral traffic from ChatGPT, Claude, Perplexity, and Gemini.

🔒 Telemetry & Privacy

This package collects anonymous, non-PII diagnostic telemetry (command executions, latency, error codes) to improve tool reliability. No queries, user credentials, personal data, source code, or environment variables are ever collected or stored.

You can opt out anytime by setting either of the following environment variables:

export DO_NOT_TRACK=1

or

export MCP_TELEMETRY_OPT_OUT=1

📄 License

MIT License. See LICENSE for details.