MCP server for interactive user feedback and command execution in AI-assisted development, by Fábio Ferreira.
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# Interactive Feedback MCP 一个功能强大的 MCP (Model Context Protocol) 服务器,为 AI 辅助开发提供交互式用户反馈和命令执行功能。 ## 🌟 主要功能 - **交互式反馈界面** - 图形用户界面,支持文字和图片反馈 - **命令执行** - 在项目目录中执行命令并实时显示输出 - **自动提交** - 可设置倒计时自动提交反馈 - **快捷回复** - 预设常用回复内容 - **图片支持** - 上传图片文件和剪贴板粘贴,自动压缩优化 ## 📸 界面预览    ## cursor配置  ## ⚡ MCP 配置 ### 使用 uvx (推荐) 在 Cursor 或其他支持 MCP 的 AI 助手中添加以下配置: ```json { "mcpServers": { "interactive-feedback-mcp": { "command": "uvx", "args": ["--from", "git+https://github.com/duolabmeng6/interactive-feedback-mcp.git", "interactive-feedback-mcp"], "timeout": 600, "autoApprove": ["interactive_feedback"] } } } ``` ### 使用 uv (本地安装) 如果您已经克隆了项目到本地: ```json { "mcpServers": { "interactive-feedback-mcp": { "command": "uv", "args": ["run", "--directory", "/path/to/interactive-feedback-mcp", "interactive-feedback-mcp"], "timeout": 600, "autoApprove": ["interactive_feedback"] } } } ``` 或者使用传统方式: ```json { "mcpServers": { "interactive-feedback-mcp": { "command": "uv", "args": ["run", "--directory", "/path/to/interactive-feedback-mcp", "python", "interactive_feedback_mcp/server.py"], "timeout": 600, "autoApprove": ["interactive_feedback"] } } } ``` ### 使用 Python (本地安装) ```json { "mcpServers": { "interactive-feedback-mcp": { "command": "python", "args": ["/path/to/interactive-feedback-mcp/server.py"], "timeout": 600, "autoApprove": ["interactive_feedback"] } } } ``` ## 🎯 提示工程规则 为了获得最佳的交互体验,建议在您的 AI 助手中添加以下规则: ### MCP Interactive Feedback 使用规则 ``` # MCP Interactive Feedback 规则 1. 在任何流程、任务、对话进行时,无论是询问、回复、或完成阶段性任务,皆必须调用 MCP interactive-feedback-mcp。 2. 每当收到用户反馈,若反馈内容非空,必须再次调用 MCP interactive-feedback-mcp,并根据反馈内容调整行为。 3. 仅当用户明确表示「结束」或「不再需要交互」时,才可停止调用 MCP interactive-feedback-mcp,流程才算结束。 4. 除非收到结束指令,否则所有步骤都必须重复调用 MCP interactive-feedback-mcp。 5. 完成任务前,必须使用 MCP interactiv…
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