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.