This project implements a Model Context Protocol (MCP) server that uses the local [gemini-cli](https://github.com/google-gemini/gemini-cli) to
MCP Gemini Web Search becomes available to MCP clients through the MCP Gemini Web Search. This project implements a Model Context Protocol (MCP) server that uses the local gemini-cli to perform Web Search Tool.
This project implements a Model Context Protocol (MCP) server that uses the local gemini-cli to perform Web Search Tool.
gemini-cli.Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.
{
"mcpServers": {
"gemini-web-search": {
"command": "node",
"args": [
"/path/to/mcp-gemini-web-search/index.js"
]
}
}
}From the project documentation. Replace placeholders and example paths before connecting.
gemini-cli.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.
A Python implementation of a Model Context Protocol (MCP) server that provides various tools for AI assistants to perform actions in a secure and controlled environment.
A MCP-based documentation crawler service
Spoken is a transcript API that turns any published podcast into clean Markdown with real speaker names — not "Speaker 1." One API call returns named, timestamped text, ready for LLMs, RAG…
{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"whoami","arguments":{}}} free no key