# Interactive Feedback MCP
一个功能强大的 MCP (Model Context Protocol) 服务器,提供交互式反馈界面,支持工作空间管理、任务追踪和检查点恢复。
## ✨ 核心特性
- 🎯 **交互式反馈界面**: 基于 PySide6 的现代化 UI,支持文本、图片等多种反馈方式
- 📁 **工作空间管理**: 完整的工作空间生命周期管理,支持阶段切换
- ✅ **任务追踪**: 强大的任务管理系统,支持依赖关系、优先级、并行执行
- 💾 **检查点恢复**: 创建、恢复、对比工作检查点,确保工作安全
- 🔄 **工作流支持**: 模板化工作流,支持自定义工作流程
- 📊 **会话管理**: 完整的会话历史记录和统计
## 🚀 快速开始
### 安装
```bash
# 国内用户推荐使用镜像加速
export UV_INDEX_URL="https://pypi.tuna.tsinghua.edu.cn/simple"
uvx feedback-mcp@latest
# 或使用 pip
pip install feedback-mcp
# 国内用户使用镜像
pip install feedback-mcp -i https://pypi.tuna.tsinghua.edu.cn/simple
```
### 配置 MCP
在你的 MCP 客户端配置文件中添加:
```json
{
"mcpServers": {
"feedback": {
"command": "uvx",
"args": ["feedback-mcp@latest", "--ide", "qoder"],
"timeout": 600,
"autoApprove": ["interactive_feedback"]
}
}
}
```
--ide 后跟的是想要打开的ide名称
### 使用示例
```python
# MCP 工具会自动调用
# AI 助手可以通过 feedback 工具与用户交互
```
## 📦 主要功能
### 1. 工作空间管理
- 创建工作空间并设置目标
- 管理工作空间的不同阶段
- 记录工作记忆和相关文件
- 支持多个并行工作空间
### 2. 任务管理
- 创建和更新任务列表
- 设置任务依赖关系和优先级
- 支持任务并行执行
- 实时任务状态追踪
### 3. 检查点系统
- 创建工作检查点快照
- 恢复到历史检查点
- 对比不同检查点的差异
- 自动收集相关文件
### 4. 工作流引擎
- 预定义工作流模板
- 自定义工作流步骤
- 工作流状态管理
- 步骤依赖和执行控制
## 🔧 系统要求
- Python >= 3.13
- PySide6 >= 6.8.0
- FastMCP >= 2.5.1
## 📝 开发
```bash
# 克隆仓库
git clone https://github.com/yourusername/interactive-feedback-mcp.git
cd interactive-feedback-mcp
# 安装开发依赖
pip install -e ".[dev]"
# 运行服务器
python -m src-min.server
```
## 🤝 贡献
欢迎提交 Issue 和 Pull Request!
## 📄 许可证
MIT License
## 🔗 相关链接
- [GitHub Repository](https://github.com/yourusername/interactive-feedback-mcp)
- [MCP Documentation](https://modelcontextprotocol.io/)
- [Issue Tracker](https://github.com/yourusername/interactive-feedback-mcp/issues)
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