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.

• 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.

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.

uvx --from git+https://github.com/philschmid/gemini-api-docs-mcp gemini-docs-mcp

Option 2: Install directly from GitHub

You can install the package directly from GitHub using pip:

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

Option 3: Manual Installation (for development)

git clone https://github.com/philschmid/gemini-api-docs-mcp.git
cd gemini-api-docs-mcp
pip install -e .
cd ..
rm -rf gemini-api-docs-mcp

Usage

Running as a Remote HTTP Server

The server runs as an HTTP server and exposes the MCP protocol at the /mcp endpoint. It respects the PORT environment variable (defaults to 8080).

# Set port (optional, defaults to 8080)
export PORT=8080

# Run the server
gemini-docs-mcp

The server will be accessible at http://localhost:8080/mcp (or your configured port).

Docker Deployment

Build and run the Docker container:

# Build the image
docker build -t gemini-docs-mcp .

# Run the container
docker run -p 8080:8080 gemini-docs-mcp

Cloud Run Deployment

Deploy to Google Cloud Run:

# Build and deploy
gcloud run deploy gemini-docs-mcp \
  --source . \
  --platform managed \
  --region us-central1 \
  --allow-unauthenticated

The server will be accessible at https://<your-service-url>/mcp.

Running in Stdio Mode (Local)

If you don't set the PORT environment variable, the server runs in stdio mode for local MCP clients:

# Don't set PORT - runs in stdio mode
gemini-docs-mcp

Configuration

The database is stored at:

• /tmp/gemini-api-docs/database.db in containerized environments

• ~/.mcp/gemini-api-docs/database.db in local environments

You can override this by setting the GEMINI_DOCS_DB_PATH environment variable.

Using with an MCP Client

For remote HTTP servers, configure your MCP client to connect via HTTP:

{
  "mcpServers": {
    "gemini-docs": {
      "url": "https://<your-service-url>/mcp"
    }
  }
}

For local development with stdio (if supported by your client):

{
  "mcpServers": {
    "gemini-docs": {
      "command": "gemini-docs-mcp"
    }
  }
}

Tools

• search_documentation(queries: list[str]): Performs a full-text search on Gemini documentation for the given list of queries (max 3).

• get_capability_page(capability: str = None): Get a list of capabilities or content for a specific one.

• get_current_model(): Get documentation for current Gemini models.

License

MIT

Test Results

We run a comprehensive evaluation harness to ensure the MCP server provides accurate and up-to-date code examples. The tests cover both Python and TypeScript SDKs.

Last updated: 2025-11-03 13:29:01

You can find the detailed test results in tests/result.json.