Gemini Docs MCP Server
This server provides search and retrieval tools for Google Gemini API documentation through an MCP (Model Context Protocol) interface.
Available Tools:
search_documentation: Performs keyword-based, full-text searches across all Gemini documentation pages using short queries (1-3 keywords maximum, max 3 queries at once)get_capability_page: Retrieves the complete content of a specific documentation page by its exact title, or call without arguments to get a master list of all available page titlesget_current_model: Quickly accesses the dedicated "Gemini Models" documentation page with details about model variants (Pro, Flash, etc.), their capabilities, versioning, and context window sizes
Key Features:
Automatic documentation updates on server startup by scraping from
ai.google.devLocal SQLite database with FTS5 full-text search indexing for efficient querying and offline access
Supports Python and TypeScript SDK documentation
Provides tools for searching and retrieving Google Gemini API documentation, including full-text search across documentation pages, listing available capabilities, and accessing current model documentation.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Gemini Docs MCP Serversearch for how to use embeddings with Gemini"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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 resultsHow it Works
Ingestion: On startup, the server fetches
https://ai.google.dev/gemini-api/docs/llms.txtto get a list of all available documentation pages.Processing: It then concurrently fetches and processes each page, extracting the text content.
Indexing: The processed content is stored in a local SQLite database with a Full-Text Search (FTS5) index for efficient querying.
Searching: When you use the
search_documentationtool, the server queries this SQLite database to find the most relevant documentation pages.
Related MCP server: Gemini Docs MCP Server
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-mcpOption 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.gitOption 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-mcpUsage
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-mcpThe 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-mcpCloud Run Deployment
Deploy to Google Cloud Run:
# Build and deploy
gcloud run deploy gemini-docs-mcp \
--source . \
--platform managed \
--region us-central1 \
--allow-unauthenticatedThe 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-mcpConfiguration
The database is stored at:
/tmp/gemini-api-docs/database.dbin containerized environments~/.mcp/gemini-api-docs/database.dbin 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.
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.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- AlicenseAqualityAmaintenanceProvides full-text search and retrieval tools for Apache Spark documentation using SQLite FTS5 with BM25 ranking. It enables AI assistants to efficiently search, filter by section, and read specific Spark documentation pages.Last updated2MIT
- FlicenseAqualityDmaintenanceEnables users to search and fetch Google's Gemini API documentation directly within an MCP-compliant environment. It provides structured access to guides and references for features like function calling, embeddings, and text generation.Last updated2
- Flicense-qualityDmaintenanceEnables AI assistants to fetch, index, and perform semantic RAG-based searches on API documentation from various sources. It provides tools for hybrid search and collection management, allowing users to access up-to-date documentation from projects like Gemini and FastMCP.Last updated
- Flicense-qualityBmaintenanceIndexes documentation sites by base URL and serves keyword search, optional semantic search, and Markdown page retrieval as MCP tools, all from a single SQLite file.Last updated
Related MCP Connectors
@latest documentation and code examples to 9000+ libraries for LLMs and AI code editors in a singl…
Provide your AI coding tools with token-efficient access to up-to-date technical documentation for…
DevDocs.io keyless docs index + entry search + content (Angular, MDN, Rust, etc.).
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/philschmid/gemini-api-docs-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server