Gemini

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This Python-based Model Context Protocol (MCP) server simplifies the integration of Gemini's powerful AI models into various development environments. Built upon FastMCP, it acts as a bridge, allowing applications like Cursor or Claude to leverage Gemini's capabilities by configuring a simple JSON setup. It supports critical environment variables for API keys, model selection, base URLs, and proxy settings, streamlining the process of connecting to Gemini services within an AI development workflow.

Características Principales

• 1 GitHub stars
• Integrates Gemini via Model Context Protocol (MCP)
• Built with FastMCP for efficient communication
• Implemented entirely in Python
• Docker image for easy deployment
• Configurable via environment variables for API key, model, base URL, and proxies

Casos de Uso

• Establishing a local MCP server for Gemini-powered applications
• Connecting Gemini to AI-powered code editors like Cursor
• Integrating Gemini with AI assistance tools such as Claude