GREB by Cheetah AI

Overview

GREB by Cheetah AI is an intelligent, MCP-native code search engine designed for modern AI coding assistants. Instead of relying on brittle regex or slow full-text indexing, GREB exposes your repositories through the Model Context Protocol (MCP), giving AI agents a structured, semantic way to discover, navigate, and understand your codebase. Developers can ask natural-language questions like “Where is the payment retry logic implemented?” or “Show me how we validate JWTs,” and GREB will precisely locate the most relevant files, symbols, and usage patterns. By integrating directly into AI copilots and command-line workflows, GREB eliminates context-window limitations and manual file hunting. It lets AI assistants pull only what they need, when they need it, while preserving your existing tools, IDEs, and Git workflows. GREB is language-agnostic and works across monoliths, microservices, and polyglot repositories, making it ideal for enterprise-scale codebases. With GREB, teams ship faster by turning AI coding assistants into truly context-aware collaborators. Onboarding becomes smoother, refactors become safer, and incident response becomes more efficient because your AI tools finally understand how your code is actually organized and used.