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MCP Deploy Server

Project description

Cloud Studio MCP 部署服务

Python Version FastAPI

Cloud Studio MCP 部署服务是一个基于FastMCP的服务器,提供Cloud Studio工作空间的管理功能,包括创建工作空间、上传文件和执行命令等操作。

功能特性

  • 创建工作空间:创建新的Cloud Studio工作空间实例
  • 文件管理:上传文件到指定工作空间
  • 命令执行:在工作空间中执行shell命令
  • MCP集成:通过MCP协议提供标准化接口

安装指南

前置要求

  • Python 3.8+
  • API_TOKEN环境变量(Cloud Studio API访问令牌)

安装步骤

  1. 克隆仓库:

    git clone <repository-url>
    cd mcp_deploy
    
  2. 创建并激活虚拟环境:

    python -m venv .venv
    source .venv/bin/activate  # Linux/macOS
    .\.venv\Scripts\activate   # Windows
    
  3. 安装依赖:

    pip install -e .
    

配置说明

在运行服务前,需要设置以下环境变量:

export API_TOKEN="your_cloud_studio_api_token"
export region="ap-shanghai"  # 可选,默认为ap-shanghai

使用说明

启动服务

python -m mcp_deploy

API 文档

服务提供以下MCP工具:

1. 创建工作空间

create_workspace() -> dict

返回示例:

{
    "workspace_key": "ws-kmhhvqnlogr48",
    "webIDE": "https://ws-kmhhv1pyvc48--ide.ap-shanghai.cloudstudio.club"
}

2. 上传文件

write_files(workspace_key: str, region: str, files: list[File]) -> str

文件格式:

class File:
    save_path: str    # 文件保存路径
    file_content: str # 文件内容(UTF-8编码)

3. 执行命令

execute_command(workspace_key: str, region: str, command: str) -> str

示例:

execute_command("ws-xxxx", "ap-shanghai", "ls -al")

开发指南

项目结构

mcp_deploy/
├── __init__.py
├── __main__.py
├── mcp_handlers.py    # 核心业务逻辑
├── models.py          # 数据模型定义
└── server.py          # FastMCP服务器实现

测试

  1. 确保已设置API_TOKEN环境变量
  2. 运行测试命令:
    python -m pytest
    

贡献

欢迎提交Pull Request或Issue报告问题。

许可证

MIT License

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