Google Search Console MCP Server

A Model Context Protocol (MCP) server that connects AI assistants (ChatGPT, Claude, custom agents) with Google Search Console data. Analyze your SEO data through natural language conversations - ask questions, get insights, and take action without navigating dashboards.

Production Endpoint: https://gsc-mcp-cloud.principal-e85.workers.dev

What Is This?

This MCP server acts as a bridge between AI assistants and the Google Search Console API. Instead of manually navigating GSC dashboards, you can ask questions like:

• "What are my top-performing keywords this month?"
• "Find pages that are losing traffic"
• "Check if my new blog post is indexed"
• "What keywords am I ranking 11-20 for that I could push to page 1?"
• "Compare my performance before and after the last algorithm update"

The AI assistant uses this MCP server to fetch real data from your GSC account and provide actionable insights.

Who Is This For?

Problems It Solves

1. Time-Consuming Manual Analysis - Ask natural language questions instead of clicking through dashboards
2. Missed Optimization Opportunities - AI identifies striking distance keywords and CTR opportunities automatically
3. Reactive SEO - Get proactive alerts about declining pages before they drop off page 1
4. Complex Data Interpretation - AI translates raw data into actionable recommendations
5. Multi-Property Management - Query across all your GSC properties in one conversation
6. Algorithm Impact Analysis - Quickly compare before/after performance around updates

Available Tools (26 Total)

OpenAI MCP Integration (2 tools)

Property Management (4 tools)

Search Analytics (5 tools)

URL Inspection (3 tools)

Sitemap Management (5 tools)

SEO Analysis Tools (7 tools)

Specialized tools for actionable SEO insights:

*Note: External backlink data is NOT available via GSC API. Use Ahrefs/SEMrush for external links.

API Limitations

Architecture

+-----------------+     +------------------+     +-----------------+
|   AI Assistant  |---->|   MCP Server     |---->|  Google Search  |
|  (ChatGPT, etc) |<----|  (Cloudflare)    |<----|  Console API    |
+-----------------+     +------------------+     +-----------------+
                               |
                               v
                        +--------------+
                        |   KV Store   |
                        | (OAuth tokens)|
                        +--------------+

Stack:

• Runtime: Cloudflare Workers (TypeScript) or local Python (FastMCP)
• Framework: Hono (web), Zod (validation)
• Protocol: MCP over SSE
• Auth: Google OAuth 2.0

Deployment Options

Option 1: Cloudflare Workers (Recommended for ChatGPT)

Endpoint: https://gsc-mcp-cloud.principal-e85.workers.dev

Setup

cd gsc-mcp-cloud
npm install

# Set OAuth credentials
npx wrangler secret put GOOGLE_CLIENT_ID
npx wrangler secret put GOOGLE_CLIENT_SECRET

# Deploy
npm run deploy

# Visit /auth to authenticate with Google

Option 2: Local Python Server (For Claude Desktop)

OAuth Authentication (Recommended)

{
  "mcpServers": {
    "gscServer": {
      "command": "/path/to/mcp-gsc/.venv/bin/python",
      "args": ["/path/to/mcp-gsc/gsc_server.py"],
      "env": {
        "GSC_OAUTH_CLIENT_SECRETS_FILE": "/path/to/client_secrets.json"
      }
    }
  }
}

Service Account Authentication

{
  "mcpServers": {
    "gscServer": {
      "command": "/path/to/mcp-gsc/.venv/bin/python",
      "args": ["/path/to/mcp-gsc/gsc_server.py"],
      "env": {
        "GSC_CREDENTIALS_PATH": "/path/to/service_account_credentials.json",
        "GSC_SKIP_OAUTH": "true"
      }
    }
  }
}

Example Prompts

Changelog

v1.3.0 - December 30, 2025, 07:05 UTC

CI/CD & Testing

• Added Vitest testing framework with 53 unit tests
• Test coverage: 80%+ for SEO analysis tools
• Added GitHub Actions workflow for automated testing on push/PR
• Added GitHub Actions workflow for automated Cloudflare Workers deployment
• Deployment triggers on changes to gsc-mcp-cloud/ directory
• Added CI status badges to README

v1.2.1 - December 30, 2025, 05:50 UTC

URL Parsing Fix

• Fixed check_page_experience and get_coverage_report to accept both comma-separated and newline-separated URL lists
• Improved usability for AI assistants passing multiple URLs
• Deployed to production

v1.2.0 - December 30, 2025, 04:30 UTC

SEO Analysis Tools

• Added 7 new specialized SEO analysis tools:
  • find_high_potential_keywords - Striking distance and CTR opportunities
  • check_page_experience - Mobile usability and crawl status
  • get_coverage_report - Comprehensive indexing analysis
  • analyze_backlinks - Page authority based on search visibility
  • spot_content_opportunities - Rising/declining query detection
  • analyze_regional_device_performance - Country and device breakdown
  • analyze_algorithm_impact - Before/after comparison for updates
• Added helper functions: calculatePercentageChange, formatChange, formatDate, getDateRange, getExpectedCTR
• Total tools increased from 19 to 26
• Tested with real GSC data from production properties

v1.1.0 - December 29, 2025, 22:00 UTC

Infrastructure Improvements

• Added FastMCP configuration for Python server
• Implemented Hono error handling middleware with structured JSON responses
• Added cache middleware for health endpoint (5 minute TTL)
• Fixed SSE body consumption error (request cloning fix)
• Improved Zod validation with custom error messages
• Set up Google OAuth 2.0 authentication flow with KV token storage
• Initial deployment to Cloudflare Workers

v1.0.0 - December 29, 2025, 18:00 UTC

Initial Release

• Core MCP server implementation
• 19 tools across 5 categories:
  • 2 OpenAI MCP integration tools
  • 4 Property management tools
  • 5 Search analytics tools
  • 3 URL inspection tools
  • 5 Sitemap management tools
• Python server with FastMCP support
• TypeScript server for Cloudflare Workers

Local Development

# TypeScript (Cloudflare Workers)
cd gsc-mcp-cloud
npm install
npm run dev

# Python (FastMCP)
cd mcp-gsc
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
python gsc_server.py

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

Repository: https://github.com/hablapro/mcp-gsc

License

MIT License - See LICENSE file for details.