广告合作
MCP.so
登录

Interactive Feedback MCP - 交互式反馈收集器

@bulice

代码仓库

基本信息

分类

其他

许可证

MIT

传输方式

stdio

作者

bulice

关于 Interactive Feedback MCP - 交互式反馈收集器

Interactive Feedback MCP Server - A tool for collecting user feedback with PySide6 interface

#interactive-feedback#feedback-collector#ai-assistant

Interactive Feedback MCP - 交互式反馈收集器 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "interactive-feedback-mcp": {
      "command": "uv",
      "args": [
        "sync"
      ]
    }
  }
}

Interactive Feedback MCP - 交互式反馈收集器 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 Interactive Feedback MCP - 交互式反馈收集器?

Interactive Feedback MCP - 交互式反馈收集器 is an MCP (Model Context Protocol) server that provides a graphical user interface for human-in-the-loop feedback during AI-assisted development. It allows users to submit text feedback, upload images, execute commands, and see real-time output, enabling collaborative development with AI tools like Cursor, Cline, and Windsurf.

How to use Interactive Feedback MCP - 交互式反馈收集器?

Clone the repository, install dependencies with uv sync or pip install -r requirements.txt, then run uv run server.py or python server.py. Configure the server in your AI tool’s MCP settings (e.g., Cursor’s mcpServers JSON) with the path to mcp_server.sh. The AI assistant can call the interactive_feedback tool to prompt the user for input.

Key features of Interactive Feedback MCP - 交互式反馈收集器

  • Two-way text feedback with AI assistants via a GUI
  • Multi-image upload or clipboard paste support
  • Real-time command execution with live output and process monitoring
  • Dark and light theme switching with responsive design
  • Project-specific configuration persistence using Qt QSettings
  • Command history and auto-execute on startup option

Use cases of Interactive Feedback MCP - 交互式反馈收集器

  • Reducing speculative high-cost tool calls by confirming intent with the user before proceeding
  • Collecting detailed human feedback during iterative code generation or debugging sessions
  • Enabling visual feedback by attaching screenshots or diagrams to AI conversations
  • Running and reviewing command outputs interactively within the AI development workflow

常见问题

1

What are the system requirements?

Python 3.11 or higher, and the server runs on Windows, macOS, and Linux. The recommended package manager is `uv`.

2

How do I configure the server for Cursor?

Add a JSON entry under `mcpServers` in Cursor’s MCP configuration, specifying the command as the full path to `mcp_server.sh`, with `timeout` 600 and `autoApprove` for `interactive_feedback`.

3

What tools does the MCP server expose?

It provides the `interactive_feedback` tool for text/image feedback and the `get_image_info` tool for image details.

4

Where are configuration settings stored?

Settings are stored per project using Qt’s `QSettings` in platform‑specific locations (e.g., Windows registry, macOS plist, Linux config files). This includes command to run, auto‑execute flag, window geometry, and UI state.

5

Is there a diagnostic tool available?

Yes, a `diagnose_mcp.py` script is included to check MCP server connectivity, verify dependencies, and generate configuration suggestions.

评论

其他 分类下的更多 MCP 服务器

Hindsight

vectorize-io

Hindsight: Agent Memory That Learns

50.4K

Handl

Handl speaks the Model Context Protocol. Your whole billing operation — projects, invoices, clients, reports, approvals — as tools any AI assistant can call, inside your autonomy rules.

Volley.sh

Volley

A good sequence diagram can solve almost any communication problem in engineering. Volley lets your agent write them as plain text, with the real request and response payloads on every arrow. It checks its own syntax wi

Lemon.io

lemon-io

Request dedicated senior developers to work on your project, write job descriptions, and prep technical interviews — all without leaving your Claude chat. Just describe what you need, and Lemon.io MCP does the rest. 1–3

🚀 Model Context Protocol (MCP) Curriculum for Beginners

microsoft

This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable,

16.7K
广告合作