Gemini CLI

Integrates with Google's Gemini models through API and CLI to provide intelligent code analysis, security auditing, and large-scale codebase assessment with automatic model routing and token-efficient processing.

This MCP server provides AI assistants with access to Google's Gemini AI models through both direct API calls and CLI integration, built by Dr Muhammad Aizat Hawari using Python with intelligent model selection that routes simple queries to Gemini Flash and complex analysis tasks to Gemini Pro. The implementation features three core tools: quick Q&A queries, focused code analysis with security and performance insights, and large-scale codebase analysis leveraging Gemini's 1M token context window, with automatic fallback from API to CLI and real-time streaming output with progress tracking. Serves developers needing AI-powered code review and analysis capabilities, teams requiring automated codebase assessment and security auditing, and organizations wanting to integrate Gemini's advanced reasoning into their development workflows with token-efficient model routing and Claude IDE integration through custom hooks.