Rapid-MLX MCP Server

How to use Rapid-MLX MCP Server

git clone https://github.com/raullenchai/Rapid-MLX.git
cd Rapid-MLX && pip install -e .

{
  "servers": {
    "filesystem": {
      "transport": "stdio",
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem", "/tmp"],
      "enabled": true,
      "timeout": 30
    },
    "sqlite": {
      "transport": "stdio",
      "command": "uvx",
      "args": ["mcp-server-sqlite", "--db-path", "data.db"],
      "enabled": false,
      "timeout": 30
    },
    "web-search": {
      "transport": "sse",
      "url": "http://localhost:3001/sse",
      "enabled": false,
      "timeout": 60
    }
  },
  "max_tool_calls": 10,
  "default_timeout": 30.0
}

What is Rapid-MLX MCP Server?

Rapid-MLX is a Python MCP server for Cursor, VS Code, Codex with uvx/pip, docker, git clone. The fastest local AI engine for Apple Silicon. 4.2x faster than Ollama, 0.08s cached TTFT, 100% tool calling. 17 tool parsers, prompt cache, reasoning separation, cloud routing. Drop-in. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.

Key capabilities

• Tool access support
• Includes SKILL.md support
• Shell commands support
• Browser use support
• Document generation support
• OpenAI provider support
• Anthropic provider support

Available tools

Technical details

Install or run Rapid-MLX using uvx/pip. Check raullenchai/Rapid-MLX for the latest setup command.

• Built for Python
• Built for Go
• Built for Rust
• Install or run with uvx/pip
• Install or run with docker
• Install or run with git clone
• Works with Cursor
• Works with VS Code

Requirements and access

Security and permissions

Review permissions before connecting any MCP server to an agent. Pay special attention to whether it can read local files, write data, call external services, or perform destructive actions.

When to use Rapid-MLX MCP Server

• Use it for connecting agents to external tools and data.
• Use it for integrations workflows.
• Use it for coding workflows.
• Use it for data workflows.
• Use it for cursor users.

Built with

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Frequently asked questions