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Enhanced MCP server for interactive user feedback and command execution in AI-assisted development, featuring dual interface support (Web UI and Desktop Application) with intelligent environment detection and cross-platform compatibility.

Project description

Cursor Feedback MCP

🔧 项目说明

基于 mcp-feedback-enhanced 项目进行定制开发,感谢原作者的贡献!

本版本修复了以下问题并新增功能:

✅ 已修复问题

  1. 超时设置问题:修复了超时时间永远是 600s 的问题,现已修复默认 24 小时超时 ,可以长时间等待反馈啦
  2. 图片上传问题:修复了无法上传图片报错序列号错误的问题,现已支持更多类型图 片 😁🎉
  3. 断网重连功能:新增断网不断链接功能,现在可以离线同一个会话等待(适合使用 手机热点为电脑提供互联网的场景)

🚀 如何使用

方式一:使用 uvx 直接安装(推荐)

# 直接使用 uvx 运行
uvx cursor-feedback-mcp

# 或者安装后使用
uv tool install cursor-feedback-mcp
cursor-feedback-mcp

方式二:在 Cursor 中配置

{
  "mcpServers": {
    "cursor-feedback-mcp": {
      "command": "uvx",
      "args": ["cursor-feedback-mcp"],
      "timeout": 86400,
      "env": {
        "MCP_DEBUG": "false",
        "MCP_WEB_HOST": "127.0.0.1",
        "MCP_WEB_PORT": "8765",
        "MCP_DESKTOP_MODE": "false",
        "MCP_LANGUAGE": "zh-CN"
      },
      "autoApprove": ["interactive_feedback"]
    }
  }
}

方式三:本地开发模式

Fork 本项目到本地,在 Cursor 中配置:

{
  "mcpServers": {
    "cursor-feedback-mcp-local": {
      "command": "uv",
      "args": [
        "run",
        "--directory",
        "/path/to/your/cursor_feedback_mcp",
        "python",
        "-m",
        "cursor_feedback_mcp"
      ],
      "timeout": 86400,
      "env": {
        "MCP_DEBUG": "false",
        "MCP_WEB_HOST": "127.0.0.1",
        "MCP_WEB_PORT": "8765",
        "MCP_DESKTOP_MODE": "false",
        "MCP_LANGUAGE": "zh-CN"
      },
      "autoApprove": ["interactive_feedback"]
    }
  }
}

注意:请将 /path/to/your/cursor_feedback_mcp 改为您本地的项目位置。

📸 界面预览

Cursor Feedback MCP 界面预览
主界面 - 支持提示管理、自动提交、会话跟踪上传图片等功能
Cursor Feedback MCP 功能展示
超时功能展示 - 智能工作流程和现代化体验

📦 安装与发布

从 PyPI 安装

# 使用 uvx 直接运行
uvx cursor-feedback-mcp

# 或使用 pip 安装
pip install cursor-feedback-mcp

# 或使用 uv 安装
uv tool install cursor-feedback-mcp

本地开发

# 克隆项目
git clone https://github.com/zhajiahe/cursor-feedback-mcp.git
cd cursor-feedback-mcp

# 安装依赖
uv sync

# 运行测试
uv run pytest

# 本地构建
uv build

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