Google Analytics MCP
An MCP server that provides [describe what your server does]
Install Google Analytics MCP
Pick your client, then add it in one click or paste the config.
~/Library/Application Support/Claude/claude_desktop_config.json{
"mcpServers": {
"google-analytics-mcp": {
"command": "uvx",
"args": [
"google-analytics-mcp"
]
}
}
}
Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.
Automated check passed— started and listed 12 tools correctly (11d ago).
Overview
Tools12
What Google Analytics MCP lets your agent do. Expand a tool for its parameters.
Security & health
What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.
Recent health check succeeded.
What it can do
From the 12 tools this server returned when we ran it; 12 declare their own safety hints.
Observed 2026-10-17 in an isolated sandbox. A description of reach, not a security audit.
Supply-chain signal
No high-severity advisories surfaced by our automated scan.
Scanned 12d ago via OSV.dev · google-analytics-mcp (PyPI)
Adoption & maintenance
Factual signals from GitHub, npm, and our automated checks — not a rating.
From the project README
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.
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