It connects directly to your Google Search Console account via the official API, letting you access key data right from AI tools like Claude Desktop
Google Search Console MCP server exists for a simple reason — assistants are far more useful when they can act on Google Search Console directly instead of describing what you should do. It connects directly to your Google Search Console account via the official API, letting you access key data right from AI tools like Claude Desktop or OpenAI Agents SDK and others.
This project provides a Model Context Protocol (MCP) server that allows Claude AI (via the Claude Desktop app) or others to interact with the Google Search Console API. You can use it to query performance data, inspect URLs, check indexing status, and more, directly from your Claude chat (or others).
venv (recommended, built into Python 3). * Google Account: With access to the Google Search Console properties you want to query. * Claude Desktop App: Installed and running.Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.
Plenty of AI and media services servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. It is maintained by metehan777; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
{
"mcpServers": {
"filesystem": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-filesystem",
"/Users/username/Desktop",
"/Users/username/Downloads"
]
},
"google-search-console": {
"command": "/Users/username/Documents/search-console-mcp/fresh_env/bin/python3",
"args": [
"-m",
"main"
],
"cwd": "/Users/username/Cursor/search-console-mcp"
}
}
}Configuration as documented by the project. Restart the client after saving.
venv (recommended, built into Python 3). * Google Account: With access to the Google Search Console properties you want to query. * Claude Desktop App: Installed and running.Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.