Indexes the entire Google Gemini API documentation into a local SQLite database with full-text search, so you can query it without leaving your editor. Scrapes ai.google.dev/gemini-api/docs on startup, processes every page, and builds an FTS5 index for fast lookups. Exposes three tools: search_documentation for full-text queries, get_capability_page to list or fetch specific docs, and get_current_model for quick access to model documentation. Runs as either a remote HTTP server (deployed to Cloud Run or similar) or in local stdio mode. The database persists to disk, so subsequent startups are faster. Useful when you're building with Gemini and need to reference embeddings syntax, model capabilities, or API parameters without context switching to a browser.
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.
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
https://ai.google.dev/gemini-api/docs/llms.txt to get a list of all available documentation pages.search_documentation tool, the server queries this SQLite database to find the most relevant documentation pages.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
You can install the package directly from GitHub using pip:
pip install git+https://github.com/philschmid/gemini-api-docs-mcp.git
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
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).
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
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.
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
The database is stored at:
/tmp/gemini-api-docs/database.db in containerized environments~/.mcp/gemini-api-docs/database.db in local environmentsYou can override this by setting the GEMINI_DOCS_DB_PATH environment variable.
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"
}
}
}
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.MIT
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.
| Metric | Value |
|---|---|
| Total Tests | 117 |
| Passed | 114 |
| Failed | 3 |
Last updated: 2025-11-03 13:29:01
You can find the detailed test results in tests/result.json.
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