MCP server for searching Google Gemini API documentation
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# Gemini Docs MCP Server A remote HTTP MCP server that provides tools to search and retrieve Google Gemini API documentation. The server exposes the MCP protocol at the `/mcp` endpoint and can be deployed to Cloud Run or other containerized platforms. It also supports local stdio mode for development. <a href="https://glama.ai/mcp/servers/@philschmid/gemini-api-docs-mcp"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@philschmid/gemini-api-docs-mcp/badge" alt="Gemini Docs Server MCP server" /> </a> - **Search Documentation**: Full-text search across all Gemini documentation pages. - **Get Capabilities**: List available documentation pages or retrieve content for a specific page. - **Get Current Model**: Quickly access documentation for current Gemini models. - **Automatic Updates**: Scrapes and updates documentation on server startup. ```mermaid sequenceDiagram participant Client as MCP Client / IDE participant Server as FastMCP Server participant DB as SQLite Database Client->>Server: call_tool("search_documentation", queries=["embeddings"]) Server->>DB: Full-Text Search for "embeddings" DB-->>Server: Return matching documentation Server-->>Client: Return formatted results ``` ## How it Works 1. **Ingestion**: On startup, the server fetches `https://ai.google.dev/gemini-api/docs/llms.txt` to get a list of all available documentation pages. 2. **Processing**: It then concurrently fetches and processes each page, extracting the text content. 3. **Indexing**: The processed content is stored in a local SQLite database with a Full-Text Search (FTS5) index for efficient querying. 4. **Searching**: When you use the `search_documentation` tool, the server queries this SQLite database to find the most relevant documentation pages. ## Installation ### Option 1: Use `uvx` (Recommended) You can use `uvx` to run the server directly without explicit installation. This is the easiest way to get started. ```bas…
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