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MCP Server Python

@lucianoayres

代码仓库

基本信息

分类

其他

许可证

MIT license

传输方式

stdio

作者

lucianoayres

关于 MCP Server Python

暂无概览

MCP Server Python 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-server-python-lucianoayres": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        ".venv"
      ]
    }
  }
}

MCP Server Python 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

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 Mcp Server Python?

Mcp Server Python is an MCP (Model Context Protocol) server built in Python that exposes two basic tools—adding numbers and retrieving an environment variable—for use by LLM-based IDEs such as Cursor AI. It demonstrates how to integrate custom tool functionality into AI-assisted development environments via the standard MCP framework.

How to use Mcp Server Python?

Install the MCP package and CLI extension (pip install mcp mcp[cli]), then run the server locally with mcp dev mcp-server.py. For integration with Cursor AI, configure a mcp.json file with absolute paths to the Python executable and server script, optionally adding environment variables like API_KEY. Once integrated, invoke the tools using natural language prompts (e.g., “add 3 and 5” or “what is my API key?”) in Cursor Composer.

Key features of Mcp Server Python

  • Exposes tools to LLM-based IDEs via MCP.
  • Provides an addition tool summing two numbers.
  • Retrieves API key from the environment variable.
  • Supports CLI for local development and testing.
  • Uses standard I/O transport for seamless communication.
  • Configurable via mcp.json for Cursor AI integration.

Use cases of Mcp Server Python

  • Perform arithmetic calculations via natural language in Cursor Composer.
  • Retrieve environment-specific API keys securely through AI prompts.
  • Prototype and test MCP server functionality locally.
  • Extend AI development environments with custom tool integrations.

常见问题

1

What dependencies are required to run Mcp Server Python?

Python 3.8 or higher, and the MCP package with CLI extension (`pip install mcp mcp[cli]`).

2

How do I test the server locally?

Run `mcp dev mcp-server.py` and use the provided browser interface to connect, list templates, and test tools.

3

How do I integrate with Cursor AI?

Create or update the `mcp.json` file with absolute paths to your Python executable and server script, and optionally define environment variables like `API_KEY`.

4

What tools are included?

The server includes two tools: `add` (returns the sum of two numbers) and `getApiKey` (returns the value of the `API_KEY` environment variable).

5

What transport does the server use?

It uses standard I/O transport for communication with development environments.

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