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mcp-site-analyst

mcp-site-analyst

by danishm

MCP Site Analyst

An MCP (Model Context Protocol) server that provides Google Analytics (GA4) and Google Search Console data as tools for AI assistants.

Features

  • 13 tools across two Google services

    • Google Analytics (GA4): Custom reports, realtime data, metadata discovery, top pages, traffic sources, demographics

    • Google Search Console: Search analytics, sitemaps, URL inspection, site listing, top queries, top pages

  • Dual transport: stdio (local) and stateless HTTP (remote)

  • Flexible auth: Service account key file, inline JSON credentials, Application Default Credentials, or CLI argument

  • Configurable GA4 Property ID: Set once at server level or per-tool call

  • Optional Bearer token auth for HTTP mode

Related MCP server: ga4-mcp

Prerequisites

  1. Google Cloud Project with these APIs enabled:

  2. Service Account with a downloaded JSON key file:

  3. Grant access to the service account:

    • GA4: Admin > Property Access Management > Add the service account email as Viewer

    • Search Console: Settings > Users and permissions > Add the service account email

Installation

npm install
npm run build

Usage

stdio mode (Claude Desktop, Gemini CLI, etc.)

# Using CLI argument
node build/index.js --key-file /path/to/key.json

# Using environment variable
GOOGLE_APPLICATION_CREDENTIALS=/path/to/key.json node build/index.js

# With a default GA4 Property ID
node build/index.js --key-file /path/to/key.json --property-id 123456789

HTTP mode

# Default port 3000
node build/index.js --http --key-file /path/to/key.json

# Custom port
node build/index.js --http --port 8080 --key-file /path/to/key.json

# With Bearer token authentication
MCP_AUTH_TOKEN=my-secret-token node build/index.js --http --key-file /path/to/key.json

The HTTP endpoint is available at POST http://localhost:3000/mcp (Streamable HTTP, stateless). A health check endpoint is available at GET http://localhost:3000/health.

Authentication

The server resolves Google credentials in this order:

Priority

Method

Description

1

--key-file <path>

CLI argument pointing to a service account JSON key file

2

GOOGLE_CREDENTIALS_JSON

Environment variable containing the full JSON key as a string (useful for containers/CI)

3

GOOGLE_APPLICATION_CREDENTIALS

Environment variable pointing to a key file path

4

Application Default Credentials

Automatic on Cloud Run, GCE, or when authenticated via gcloud auth application-default login

Claude Desktop Configuration

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "site-analyst": {
      "command": "node",
      "args": [
        "/absolute/path/to/mcp-site-analyst/build/index.js",
        "--key-file",
        "/absolute/path/to/key.json",
        "--property-id",
        "YOUR_GA4_PROPERTY_ID"
      ]
    }
  }
}

Gemini CLI Configuration

Add to your .gemini/settings.json:

{
  "mcpServers": {
    "site-analyst": {
      "command": "node",
      "args": [
        "/absolute/path/to/mcp-site-analyst/build/index.js",
        "--key-file",
        "/absolute/path/to/key.json"
      ]
    }
  }
}

Remote HTTP Configuration

If deployed to a remote server (e.g. Cloud Run), configure your client to use the HTTP endpoint:

{
  "mcpServers": {
    "site-analyst": {
      "httpUrl": "https://your-service-url/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_AUTH_TOKEN"
      }
    }
  }
}

Deploying to Cloud Run

A deployment script is included for Google Cloud Run.

Setup

# Copy the example env file and fill in your values
cp .env.example .env

# Edit .env with your GCP project ID, region, and GA4 property ID

See .env.example for all available configuration options.

Deploy

# Deploy with Cloud Build (no local Docker required)
./deploy.sh --cloud-build

# Deploy with local Docker build
./deploy.sh

# Deploy with Bearer token auth enabled
./deploy.sh --token "my-secret-token"

On Cloud Run the server uses Application Default Credentials automatically via the configured service account — no key file is needed.

Tools Reference

Google Analytics (GA4)

Tool

Description

ga4_run_report

Run a custom report with flexible dimensions, metrics, date ranges, filters, and sorting

ga4_realtime_report

Get real-time active user data (last 30 minutes)

ga4_get_metadata

Discover all available dimensions and metrics

ga4_top_pages

Shortcut: Top pages by pageviews

ga4_top_traffic_sources

Shortcut: Top traffic sources by sessions

ga4_user_demographics

Shortcut: User breakdown by country/city/language

Google Search Console

Tool

Description

gsc_search_analytics

Query search performance (clicks, impressions, CTR, position) with filters

gsc_list_sitemaps

List all submitted sitemaps

gsc_get_sitemap

Get details for a specific sitemap

gsc_inspect_url

Inspect a URL's index status and mobile usability

gsc_list_sites

List all sites accessible by the service account

gsc_top_queries

Shortcut: Top search queries by clicks

gsc_top_pages

Shortcut: Top pages by clicks in search

Development

# Run in dev mode (no build step needed)
npx tsx src/index.ts --key-file /path/to/key.json

# Build
npm run build

# Test with MCP Inspector
npx @modelcontextprotocol/inspector node build/index.js --key-file /path/to/key.json

License

MIT

Available Tools

13 tools
ga4_get_metadataA

List all available dimensions and metrics for a GA4 property. Use this to discover what fields are available before running reports.

Inputs: filter, propertyId.

ga4_realtime_reportA

Get real-time active users and metrics from GA4. Shows data from the last 30 minutes.

Inputs: limit, metrics, dimensions, propertyId.

ga4_run_reportA

Run a custom GA4 report with flexible dimensions, metrics, and date ranges. Use ga4_get_metadata to discover available dimensions and metrics first.

Inputs: endDate (required), metrics (required), startDate (required), limit, +6 more.

ga4_top_pagesA

Get the top pages by page views for a GA4 property. A convenient shortcut for a common report.

Inputs: limit, endDate, startDate, propertyId.

ga4_top_traffic_sourcesA

Get top traffic sources for a GA4 property, broken down by source/medium.

Inputs: limit, endDate, startDate, propertyId.

ga4_user_demographicsA

Get user demographics breakdown (country, city, or language) for a GA4 property.

Inputs: limit, endDate, dimension, startDate, +1 more.

gsc_get_sitemapB

Get detailed information about a specific sitemap.

Inputs: siteUrl (required), feedpath (required).

gsc_inspect_urlA

Inspect a URL in Google Search Console. Returns indexing status, crawl info, mobile usability, and rich results status. Note: daily quotas apply.

Inputs: siteUrl (required), inspectionUrl (required), languageCode.

gsc_list_sitemapsA

List all sitemaps submitted to Google Search Console for a site.

Inputs: siteUrl (required).

gsc_list_sitesA

List all sites the service account has access to in Google Search Console.

Inputs: no named parameters.

gsc_search_analyticsB

Query Google Search Console search analytics data. Returns clicks, impressions, CTR, and average position. Can be broken down by query, page, country, device, or date.

Inputs: endDate (required), siteUrl (required), startDate (required), type, +5 more.

gsc_top_pagesB

Get top pages by clicks in Google Search for a site. A convenient shortcut.

Inputs: siteUrl (required), limit, endDate, startDate.

gsc_top_queriesB

Get top search queries by clicks for a site. A convenient shortcut for common analysis.

Inputs: siteUrl (required), limit, endDate, startDate.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A3.9/5.0

    Scored across 13 tools

    Disambiguation5/5

    Tools are cleanly separated by service prefix (ga4_ vs gsc_) and each targets a distinct function. Even the top_pages tools are unambiguous because one is GA4 page views and the other is GSC search clicks, with clear descriptions noting they are conveniences over more general reporting tools.

    Naming Consistency5/5

    All tools follow a consistent lower_snake_case pattern with service prefixes, and the action or data focus is clear. While some names omit explicit verbs (e.g., ga4_top_pages), the pattern is uniform across the set, making it easy to infer behavior.

    Tool Count5/5

    13 tools is well within the ideal range for a focused analytics server, covering both GA4 and GSC without redundancy. Each tool earns its place by providing a distinct, useful capability for site analysis.

    Completeness4/5

    The tool surface covers core analytics needs for both GA4 (demographics, realtime, custom reports, metadata, common metrics) and GSC (search performance, sitemaps, URL inspection, site listing). Minor gaps exist, such as no explicit GA4 property listing or advanced GSC sitemap submission, but these do not block typical analysis workflows.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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