Rapid-MLX

Why we included this project

Running local LLMs on a Mac usually means waiting through model startup and fighting with tool-calling reliability. Rapid-MLX addresses both: it is a local inference engine built for Apple Silicon that exposes an OpenAI- and Anthropic-compatible API, so existing tools like Claude Code, Cursor, or Aider can point at a machine-local model without changing their setup. Alongside the speed, it includes parsers that get models to emit structured function calls reliably, separates reasoning tokens from the main response, and keeps a prompt cache that cuts latency on repeated requests. When you want to hand a request to a hosted provider, there is a cloud-routing option as a fallback. For developers and small teams on M-series laptops who want private, offline serving without a heavy container stack, this is a practical drop-in replacement for the usual local servers.