Gemini MCP Server

A Model Context Protocol server that provides web search capabilities powered by Google's Gemini API. This server enables LLMs to perform intelligent web searches and return synthesized responses with citations.

Available Tools:

search_web - Performs a web search using Gemini and returns synthesized results with citations
- query (string, required): The search query to execute

Example Response:

{
  "text": "Recent advancements in AI include breakthrough developments in large language models, computer vision, and autonomous systems...",
  "web_search_queries": ["latest AI developments 2024", "AI breakthroughs"],
  "citations": [
    {
      "url": "https://example.com/ai-news",
      "title": "Latest AI Developments 2024",
      "text_content": "Summary of recent AI advances..."
    },
    ...
  ]
}

Installation

pip install git+https://github.com/philschmid/gemini-mcp-server.git

Authentication

STDIO mode: Uses GEMINI_API_KEY environment variable
HTTP mode: Requires Bearer token in Authorization header

Running the Server

STDIO Mode (Local/Direct Integration)

GEMINI_API_KEY="your_gemini_api_key_here" gemini-mcp --transport stdio

HTTP Mode (Network Access)

gemini-mcp --transport streamable-http

The server will start on http://0.0.0.0:8000/mcp

Usage Examples

Add to your mcpServers configuration:

STDIO Mode:

{
  "mcpServers": {
    "gemini-search": {
      "command": "gemini-mcp",
      "args": ["--transport", "stdio"],
      "env": {
        "GEMINI_API_KEY": "your_gemini_api_key_here"
      }
    }
  }
}

With MCP Inspector

Start the server and test your server using the MCP inspector:

npx @modelcontextprotocol/inspector

License

This project is licensed under the MIT License.

This server cannot be installed

security - not tested

license - permissive license

quality - not tested

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

A Model Context Protocol server that enables LLMs to perform web searches using Google's Gemini API and return synthesized responses with citations.

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