Gemini DeepSearch MCP

# Gemini DeepSearch MCP Gemini DeepSearch MCP is an automated research agent that leverages Google Gemini models and Google Search to perform deep, multi-step web research. It generates sophisticated queries, synthesizes information from search results, identifies knowledge gaps, and produces high-quality, citation-rich answers. ## Features - **Automated multi-step research** using Gemini models and Google Search - **FastMCP integration** for both HTTP API and stdio deployment - **Configurable effort levels** (low, medium, high) for research depth - **Citation-rich responses** with source tracking - **LangGraph-powered workflow** with state management ## Usage ### Development Server (HTTP + Studio UI) Start the LangGraph development server with Studio UI: ```bash make dev ``` ### Local MCP Server (stdio) Start the MCP server with stdio transport for integration with MCP clients: ```bash make local ``` ### Testing Run the test suite: ```bash make test ``` Test the MCP stdio server: ```bash make test_mcp ``` Use MCP inspector ```bash make inspect ``` With Langsmith tracing ```bash GEMINI_API_KEY=AI******* LANGSMITH_API_KEY=ls******* LANGSMITH_TRACING=true make inspect ``` ## API The `deep_search` tool accepts: - **query** (string): The research question or topic to investigate - **effort** (string): Research effort level - "low", "medium", or "high" - **Low**: 1 query, 1 loop, Flash model - **Medium**: 3 queries, 2 loops, Flash model - **High**: 5 queries, 3 loops, Pro model ### Return Format **HTTP MCP Server** (Development mode): - **answer**: Comprehensive research response with citations - **sources**: List of source URLs used in research **Stdio MCP Server** (Claude Desktop integration): - **file_path**: Path to a JSON file containing the research results The stdio MCP server writes results to a JSON file in the system temp directory to optimize token usage. The JSON file contains the same `answer` and `sources` data as the HTTP version, but is accessed via file path rather than returned directly. ## Requirements - Python 3.12+ - `GEMINI_API_KEY` environment variable ## Installation Install directly using uvx: ```bash uvx install gemini-deepsearch-mcp ``` ## Claude Desktop Integration To use the MCP server with Claude Desktop, add this configuration to your Claude Desktop config file: ### macOS Edit `~/Library/Application Support/Claude/claude_desktop_config.json`: ```json { "mcpServers": { "gemini-deepsearch": { "command": "uvx", "args": ["gemini-deepsearch-mcp"], "env": { "GEMINI_API_KEY": "your-gemini-api-key-here" }, "timeout": 180000 } } } ``` ### Windows Edit `%APPDATA%/Claude/claude_desktop_config.json`: ```json { "mcpServers": { "gemini-deepsearch": { "command": "uvx", "args": ["gemini-deepsearch-mcp"], "env": { "GEMINI_API_KEY": "your-gemini-api-key-here" }, "timeout": 180000 } } } ``` ### Linux Edit `~/.config/claude/claude_desktop_config.json`: ```json { "mcpServers": { "gemini-deepsearch": { "command": "uvx", "args": ["gemini-deepsearch-mcp"], "env": { "GEMINI_API_KEY": "your-gemini-api-key-here" }, "timeout": 180000 } } } ``` **Important:** - Replace `your-gemini-api-key-here` with your actual Gemini API key - Restart Claude Desktop after updating the configuration - Set ample timeout to avoid `MCP error -32001: Request timed out` ### Alternative: Local Development Setup For development or if you prefer to run from source: ```json { "mcpServers": { "gemini-deepsearch": { "command": "uv", "args": ["run", "python", "main.py"], "cwd": "/path/to/gemini-deepsearch-mcp", "env": { "GEMINI_API_KEY": "your-gemini-api-key-here" } } } } ``` Replace `/path/to/gemini-deepsearch-mcp` with the actual absolute path to your project directory. Once configured, you can use the `deep_search` tool in Claude Desktop by asking questions like: - "Use deep_search to research the latest developments in quantum computing" - "Search for information about renewable energy trends with high effort" ## Agent Source The deep search agent is from the [Gemini Fullstack LangGraph Quickstart](https://github.com/google-gemini/gemini-fullstack-langgraph-quickstart) repository. ## License MIT