This project provides an MCP (Model Context Protocol) server implementation for Google's Gemini API, enabling developers to integrate Gemini's advanced AI capabilities directly into their development environments. It targets users of MCP-compatible clients like Claude Desktop, Cursor, and Windsurf, offering seamless access to Gemini's features with full parameter control, thereby enhancing productivity and AI-assisted workflows.

How It Works

The server acts as a bridge, translating requests from MCP-compatible clients into calls to the Google Gemini API. It utilizes a standard stdio communication protocol for broad compatibility. The implementation is built with TypeScript and ESM, supporting Gemini 2.5 series models with features like large context windows (up to 2M tokens), JSON mode, and Google Search grounding, offering a modern and robust integration.

Quick Start & Requirements

• Primary install/run command: Integrated via MCP client configuration using npx -y github:aliargun/mcp-server-gemini.
• Non-default prerequisites: A Google Gemini API key obtained from Google AI Studio is mandatory. Requires an MCP-compatible client (e.g., Claude Desktop, Cursor, Windsurf).
• Estimated setup time: Minimal, primarily involving API key setup and client configuration.
• Relevant pages: Google AI Studio, Usage Guide, Parameters Reference.

Highlighted Details

• Supports Gemini 2.5 Pro (2M tokens) and Gemini 2.5 Flash (1M tokens) with advanced capabilities including reasoning, JSON mode, and grounding.
• Offers six core tools: text generation, image analysis, token counting, model listing, embeddings, and a self-documenting help system.
• Implements full MCP protocol via stdio for seamless integration with various IDEs and clients.
• Features a built-in, self-documenting help system accessible directly within the editor, reducing reliance on external documentation.

Maintenance & Community

The project is under active development, with regular updates planned to incorporate new Gemini features. A contributing guide is available for interested parties. Specific community channels (like Discord/Slack) or notable contributors are not detailed in the provided README.

Licensing & Compatibility

• License type: MIT License.
• Compatibility notes: The MIT license permits commercial use and integration within closed-source projects.

Limitations & Caveats

Operation is dependent on the availability and potential costs associated with the Google Gemini API. Users must manage their API keys securely, as they are configured via environment variables. The effectiveness of the integration relies on the correct setup within the chosen MCP-compatible client.