Talk to your Google Search Console from Claude, Cursor, or any MCP client.
Search Console Mcp is an MCP project maintained in the sudomichael/search-console-mcp repository. The maintainer describes its purpose as “Talk to your Google Search Console from Claude, Cursor, or any MCP client”. Read the project documentation for the complete scope.
The documented npm package is search-console-mcp-server. The configuration below comes from the maintainer’s example; adapt its paths and account values to your environment.
Project documentation · Repository · Discovery listing. This profile records the public documentation checked on 2026-10-08.
Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.
| Tool | What it does |
|---|---|
| list_properties | Your GSC properties (call first — gives exact siteUrl values) |
| query_search_analytics | Clicks / impressions / CTR / position by query, page, date, country, device — filters, pagination, and every traffic source including Google Discover |
| compare_periods | Biggest movers, computed for you: this period vs the prior one, per-page or per-query deltas, sorted by change |
| inspect_url | Google's index status for a URL: indexed or not, why, chosen canonical, last crawl |
| inspect_urls | The same, batched — up to 10 URLs in one call for indexing audits |
| list_sitemaps | Submitted sitemaps with status |
{
"mcpServers": {
"gsc": {
"command": "npx",
"args": [
"-y",
"search-console-mcp-server"
]
}
}
}From the project documentation. Replace placeholders and example paths before connecting.
Retrieve public web pages as readable Markdown with the reference Fetch MCP server, including pagination for longer responses.
Use Firecrawl MCP to retrieve website content and extract information for research through Firecrawl’s API-backed web tools.
The original Chromium automation reference server — simple, screenshot-driven browser control.
Puppeteer-powered browser control that drives pages from the accessibility tree instead of pixels.
Automates browsers and APIs, enabling Large Language Models (LLMs) to interact with web pages for tasks like screenshot capture and JavaScript
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.