Google Search Console MCP Server

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Connect Google Search Console to MCP clients such as Claude Desktop, Cursor, and Codex CLI. This lets your AI assistant read search performance, find SEO opportunities, and diagnose page indexing issues.

You do not need to remember tool parameters. In most cases, you can paste a site or page URL into the chat, and the AI client will match it to the right Search Console property before querying data.

What It Can Do

• Generate SEO weekly reports with clicks, impressions, CTR, average position, and trend changes.
• Find pages with high impressions but low CTR, then suggest title and snippet improvements.
• Show which search queries bring traffic to a specific page.
• Compare performance before and after a redesign, migration, or content update.
• Check whether a page is indexed by Google, including canonical, robots, crawl, and rich results details.

This project only reads and analyzes Search Console data. It does not add or remove sites, and it does not submit or delete Sitemaps.

For AI Coding Agents

Use this flow when you operate the MCP server from an AI agent:

1. Call get_capabilities to confirm that the server is reachable and authenticated.
2. Call list_properties before any site-specific request. Use the exact site_url it returns; do not infer or rewrite Search Console property strings.
3. For traffic and ranking questions, use Search Analytics tools such as get_performance_overview, get_search_analytics, get_search_by_page_query, compare_search_periods, or get_advanced_search_analytics.
4. For indexing, canonical, robots, crawl, or rich results questions, use URL Inspection tools such as inspect_url_enhanced, batch_url_inspection, or check_indexing_issues.
5. Sort or rank returned Search Analytics rows locally in the agent when needed. The Search Console API does not support arbitrary server-side metric sorting.
6. Treat URL Inspection results as Google's indexed-view data, not as a live crawl of the current page.

Requirements

You need:

• Node.js 20 or newer.
• A Google Cloud project with the Search Console API enabled.
• Access to the target site in Google Search Console.
• Either an OAuth Desktop Client JSON file or a Service Account JSON key.

Installation

Using npm:

npm install
npm run build

Or using pnpm:

pnpm install
pnpm build

Run in development mode:

npm run dev

Run the built server:

npm start

The built entry point is dist/index.js. When installed as a package, the binary name is google-search-console-mcp.

Authentication

OAuth

OAuth is the recommended option for local use because it authorizes with your own Google account.

1. In Google Cloud Console, select an existing project or create a new one.
2. Enable the Search Console API for that project.
3. Open Credentials and create an OAuth client ID.
4. Complete the OAuth consent screen setup when prompted, then choose Desktop app as the client type.
5. Download the client secrets JSON and keep it in a stable location, such as ~/Documents/client_secrets.json.
6. Start the server with the client secrets file:

GSC_OAUTH_CLIENT_SECRETS_FILE=/absolute/path/to/client_secrets.json npm run dev