Rapid-MLX MCP Server
raullenchai/Rapid-MLX
[](https://agentrank-ai.com/tool/raullenchai--Rapid-MLX/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) Rapid-MLX is an open-source (Apache 2.0) OpenAI- and Anthropic-compatible LLM inference server for Apple Silicon, built on MLX, focused on reliable tool calling for coding agents. Up to 4× faster than Apple's MLX (mlx-lm) on the same weights.
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
raullenchai/Rapid-MLX is a Python tool. Rapid-MLX is an open-source (Apache 2.0) OpenAI- and Anthropic-compatible LLM inference server for Apple Silicon, built on MLX, focused on reliable tool calling for coding agents. Up to 4× faster than Apple's MLX (mlx-lm) on the same weights. Topics: apple-silicon, local-llm, macos, mlx, tool-calling, ollama-alternative, claude-code, anthropic-api, coding-agents, continuous-batching, inference-server, llm-inference, llm-server, local-ai, omlx-alternative, openai-compatible, lm-studio-alternative, mcp, mlx-lm, speculative-decoding.
Ranked #161 out of 24846 indexed tools.
In the top 1% of all indexed tools.
Has 3,973 GitHub stars.
Has 53 contributors.
Actively maintained with commits in the last week.
Ecosystem
Score Breakdown
3,973 stars → well-known project
Last commit 7d ago → actively maintained
750/766 issues closed → responsive maintainer
53 contributors → active community
No dependents → no downstream usage
1,627 weekly installs → gaining traction
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
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From the README
<p align="center"> </p> <h1 align="center">Rapid-MLX</h1> <p align="center"> <strong>Rapid-MLX is an open-source (Apache 2.0) OpenAI- and Anthropic-compatible LLM inference server for Apple Silicon, built on MLX, focused on reliable tool calling for coding agents.</strong> <br> <strong>Up to 4× faster than Apple's MLX (mlx-lm), 1.5× on a typical task — same model, same weights.</strong> <br> <em>Decode speed, Qwen3.5-9B 4-bit on a Mac mini M4 Pro, greedy decoding, both servers at their defaults — <a href="https://rapidmlx.com/compare/mlx-lm">per-task results, method, and raw data</a>.</em> </p> <p align="center"> <a href="https://pypi.org/project/rapid-mlx/"></a> <a href="https://formulae.brew.sh/formula/rapid-mlx"></a> <a href="https://www.python.org/downloads/"></a> <a href="https://support.apple.com/en-us/HT211814"></a> <a href="https://github.com/raullenchai/Rapid-MLX/blob/main/LICENSE"></a> </p> <p align="center"> <a href="https://github.com/raullenchaRead full README on GitHub →
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