click-mcp

Name: click-mcp
Author: crowecawcaw

@crowecawcaw

代码仓库

关于 click-mcp

Turn click CLIs into MCP servers with one line of code

基本信息

分类

其他

许可证

MIT

运行时

python

传输方式

stdio

发布者

crowecawcaw

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "click-mcp": {
      "command": "python",
      "args": [
        "my_app.py",
        "mcp"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is click-mcp?

click-mcp is a Python library that extends Click applications with Model Context Protocol (MCP) support, allowing AI agents to discover and interact with CLI tools programmatically. It provides a simple decorator that converts Click commands into MCP tools.

How to use click-mcp?

Install via pip (pip install click-mcp), then decorate your Click group with @click_mcp(). Run the MCP server using python my_app.py mcp (or a custom command name if configured). The decorator automatically converts Click commands into MCP tools with named parameters and dot‑notation for nested groups.

Key features of click-mcp

Simple @click_mcp decorator syntax
Automatic conversion of Click commands to MCP tools
Support for nested command groups
Support for positional arguments
Stdio‑based MCP server for easy integration

Use cases of click-mcp

Turn any existing Click CLI into an MCP‑compatible tool
Allow AI agents to invoke CLI commands with structured parameters
Expose complex nested command hierarchies as discoverable MCP tools

FAQ from click-mcp

What is the Model Context Protocol (MCP)?

MCP is an open standard for AI agents to interact with tools and applications in a structured way.

What are the dependencies or runtime requirements?

click-mcp requires Python and the Click library. The README assumes a standard Python environment.

How can I customize the MCP command name?

Use the command_name parameter in the @click_mcp decorator, e.g. @click_mcp(command_name="start-mcp").

How are command errors handled?

When a Click command raises an exception, click-mcp captures the error and returns it as part of the MCP response, enabling AI agents to handle errors gracefully.