Gemini CLI Orchestrator

Provides strategic metaprompting guidance for Google's Gemini CLI through intelligent frameworks that teach agents sequential analysis workflows, ReAct loops, and synthesis strategies optimized for Gemini's 1M+ token context window without executing commands directly.

A pure metaprompting MCP server that teaches AI agents how to collaborate effectively with Google's Gemini CLI through strategic guidance rather than direct execution. Built by Danny Nguyen, this implementation provides no execution logic whatsoever - instead it returns intelligent prompts and frameworks that guide agents through sequential analysis workflows, ReAct loops, and synthesis strategies optimized for Gemini's 1M+ token context window. The server emphasizes Gemini 2.5 Flash model usage for better availability and cost-effectiveness, while teaching agents advanced techniques like complete subsystem aggregation, iterative reasoning patterns, and multi-perspective analysis synthesis for security reviews, architecture analysis, and debugging workflows.