Google Researcher MCP Server

What is Google Researcher MCP Server?

Google Researcher MCP Server gives AI assistants real-time web research abilities via Google Search, content scraping, and Gemini AI analysis. It implements the Model Context Protocol (MCP) and uses persistent caching to reduce API costs and improve performance. The server is built for developers integrating research capabilities into MCP‑compatible AI clients.

How to use Google Researcher MCP Server?

Clone the repository, install dependencies, copy .env.example to .env, and fill in your Google Custom Search API key, Custom Search Engine ID, and Gemini API key. Run in development mode with npm run dev or build and run production with npm run build && npm start. The server provides four tools – google_search, scrape_page, analyze_with_gemini, and research_topic – callable over STDIO or HTTP+SSE transports.

Key features of Google Researcher MCP Server

• Four research tools: search, scrape, analyze, and combined workflow
• Persistent caching (memory + disk) for repeated queries
• Session resumption support for web clients
• Dual transport: STDIO and HTTP+SSE
• Management API endpoints for cache and event store statistics
• OAuth 2.1 authorization with granular scope control

Use cases of Google Researcher MCP Server

• Enable an AI coding assistant to look up current web information during development
• Automate research workflows that collect, scrape, and summarize multiple sources
• Build a conversational agent that answers questions using real‑time search results
• Reduce API costs by caching identical search and analysis requests