mcp-feedback-enhanced-tuning-mbpr 2.4.2

Enhanced MCP server for interactive user feedback and command execution in AI-assisted development, featuring dual UI support (Qt GUI and Web UI) with intelligent environment detection and AI conversation end detection.

MCP Feedback Enhanced Tuning MBPR

🌐 Language / 語言切換: English | 繁體中文 | 简体中文

Original Author: Fábio Ferreira | Original Project ⭐ Enhanced Fork: Minidoracat Tuning MBPR: MBPR | GitHub | Website UI Design Reference: sanshao85/mcp-feedback-collector

🎯 Core Concept

This is an MCP server that establishes feedback-oriented development workflows, perfectly adapting to local, SSH Remote environments (Cursor SSH Remote, VS Code Remote SSH), and WSL (Windows Subsystem for Linux) environments. By guiding AI to confirm with users rather than making speculative operations, it can consolidate multiple tool calls into a single feedback-oriented request, dramatically reducing platform costs and improving development efficiency.

Supported Platforms: Cursor | Cline | Windsurf | Augment | Trae

🎯 About This Tuning

This is a tuned version of the original MCP Feedback Enhanced, optimized by MBPR with specific improvements for AI conversation flow and user experience.

🔧 Tuning Credits

• Tuned by: MBPR - AI Development & Optimization Specialist
• GitHub: https://github.com/mpbrcc
• Website: https://mbpr.cc
• Original Project: Based on MCP Feedback Enhanced by Fábio Ferreira

✨ What's New in This Tuning

• 🤖 AI Conversation End Detection - Automatically detects when AI asks "Would you like me to keep going?"
• ⏱️ Extended Timeout - 40% longer timeout (600s → 840s) for better user experience
• 🎯 Smart Auto-Trigger - Configurable automatic MCP feedback triggering
• 🔧 Enhanced Package - Separate package (mcp-feedback-enhanced-tuning-mbpr) to avoid conflicts
• 📋 Multi-language Documentation - Complete documentation in English, Chinese (Simplified & Traditional)

🎨 MBPR Optimization Philosophy

MBPR focuses on creating seamless AI-human interaction workflows. This tuning specifically addresses common pain points in AI-assisted development:

• Conversation Flow: Eliminates the need for manual MCP calls when AI reaches decision points
• User Experience: Extended timeouts give users more time for thoughtful responses
• Reliability: Separate package ensures stability and compatibility

🔄 Workflow

1. AI Call → mcp-feedback-enhanced
2. Environment Detection → Auto-select appropriate interface
3. User Interaction → Command execution, text feedback, image upload
4. Feedback Delivery → Information returns to AI
5. Process Continuation → Adjust or end based on feedback

🌟 Key Features

🖥️ Dual Interface System

• Qt GUI: Native experience for local environments, modular refactored design
• Web UI: Modern interface for remote SSH and WSL environments, brand new architecture
• Smart Switching: Auto-detect environment (local/remote/WSL) and choose optimal interface

🎨 Brand New Interface Design (v2.1.0)

• Modular Architecture: Both GUI and Web UI adopt modular design
• Centralized Management: Reorganized folder structure for easier maintenance
• Modern Themes: Improved visual design and user experience
• Responsive Layout: Adapts to different screen sizes and window dimensions

🖼️ Image Support

• Format Support: PNG, JPG, JPEG, GIF, BMP, WebP
• Upload Methods: Drag & drop files + clipboard paste (Ctrl+V)
• Auto Processing: Smart compression to ensure 1MB limit compliance

🌏 Multi-language

• Three Languages: English, Traditional Chinese, Simplified Chinese
• Smart Detection: Auto-select based on system language
• Live Switching: Change language directly within interface

✨ WSL Environment Support (v2.2.5)

• Auto Detection: Intelligently identifies WSL (Windows Subsystem for Linux) environments
• Browser Integration: Automatically launches Windows browser in WSL environments
• Multiple Launch Methods: Supports cmd.exe, powershell.exe, wslview and other browser launch methods
• Seamless Experience: WSL users can directly use Web UI without additional configuration

🤖 AI Conversation End Detection (v2.4.0 New Feature)

• Smart Detection: Automatically detects AI conversation ending phrases like "Would you like me to keep going?"
• Auto Trigger: Automatically opens MCP feedback when conversation end is detected
• Configurable: Can be controlled via MCP_AUTO_TRIGGER environment variable
• Extended Timeout: Default timeout increased by 40% (from 600s to 840s) for better user experience

🌐 SSH Remote Environment Support (v2.3.0 New Feature)

• Smart Detection: Automatically identifies SSH Remote environments (Cursor SSH Remote, VS Code Remote SSH, etc.)
• Browser Launch Guidance: Provides clear solutions when browser cannot launch automatically
• Port Forwarding Support: Complete port forwarding setup guidance and troubleshooting
• MCP Integration Optimization: Improved integration with MCP system for more stable connection experience
• Detailed Documentation: SSH Remote Environment Usage Guide
• 🎯 Auto-focus Input Box: Automatically focus on feedback input box when window opens, improving user experience (Thanks @penn201500)

🖥️ Interface Preview

Qt GUI Interface (Refactored Version)

Qt GUI Interface - Modular refactoring, supporting local environments

Web UI Interface (Refactored Version)

Web UI Interface - Brand new architecture, suitable for SSH Remote environments

Keyboard Shortcuts

• Ctrl+Enter (Windows/Linux) / Cmd+Enter (macOS): Submit feedback (supports both main keyboard and numpad)
• Ctrl+V (Windows/Linux) / Cmd+V (macOS): Directly paste clipboard images

🚀 Quick Start

1. Installation & Testing

# Install uv (if not already installed)
pip install uv

# Quick test
uvx mcp-feedback-enhanced-tuning-mbpr@latest test

2. MCP Configuration

Basic Configuration (suitable for most users):

{
  "mcpServers": {
    "mcp-feedback-enhanced-tuning-mbpr": {
      "command": "uvx",
      "args": ["mcp-feedback-enhanced-tuning-mbpr@latest"],
      "timeout": 600,
      "autoApprove": ["interactive_feedback"]
    }
  }
}

Advanced Configuration (custom environment needed):

{
  "mcpServers": {
    "mcp-feedback-enhanced-tuning-mbpr": {
      "command": "uvx",
      "args": ["mcp-feedback-enhanced-tuning-mbpr@latest"],
      "timeout": 600,
      "env": {
        "FORCE_WEB": "true",
        "MCP_DEBUG": "false",
        "MCP_AUTO_TRIGGER": "true"
      },
      "autoApprove": ["interactive_feedback"]
    }
  }
}

3. Prompt Engineering Setup

For best results, add these rules to your AI assistant:

# MCP Interactive Feedback Rules

1. During any process, task, or conversation, whether asking, responding, or completing stage tasks, must call MCP mcp-feedback-enhanced.
2. When receiving user feedback, if feedback content is not empty, must call MCP mcp-feedback-enhanced again and adjust behavior based on feedback.
3. Only when user explicitly indicates "end" or "no more interaction needed" can you stop calling MCP mcp-feedback-enhanced, then the process is complete.
4. Unless receiving end command, all steps must repeatedly call MCP mcp-feedback-enhanced.
5. Before completing the task, use the MCP mcp-feedback-enhanced to ask the user for feedback.

⚙️ Advanced Settings

Environment Variables

Variable	Purpose	Values	Default
FORCE_WEB	Force use Web UI	true/false	false
MCP_DEBUG	Debug mode	true/false	false
MCP_WEB_PORT	Web UI port	1024-65535	8765
MCP_AUTO_TRIGGER	Auto-trigger on AI conversation end	true/false	true

Testing Options

# Version check
uvx mcp-feedback-enhanced-tuning-mbpr@latest version       # Check version

# Interface-specific testing
uvx mcp-feedback-enhanced-tuning-mbpr@latest test --gui    # Quick test Qt GUI
uvx mcp-feedback-enhanced-tuning-mbpr@latest test --web    # Test Web UI (auto continuous running)

# Debug mode
MCP_DEBUG=true uvx mcp-feedback-enhanced-tuning-mbpr@latest test

Developer Installation

git clone https://github.com/Minidoracat/mcp-feedback-enhanced.git
cd mcp-feedback-enhanced
uv sync

Local Testing Methods

# Method 1: Standard test (recommended)
uv run python -m mcp_feedback_enhanced test

# Method 2: Complete test suite (macOS and Windows dev environment)
uvx --with-editable . mcp-feedback-enhanced-tuning-mbpr test

# Method 3: Interface-specific testing
uvx --with-editable . mcp-feedback-enhanced-tuning-mbpr test --gui    # Quick test Qt GUI
uvx --with-editable . mcp-feedback-enhanced-tuning-mbpr test --web    # Test Web UI (auto continuous running)

Testing Descriptions

• Standard Test: Complete functionality check, suitable for daily development verification
• Complete Test: Deep testing of all components, suitable for pre-release verification
• Qt GUI Test: Quick launch and test of local graphical interface
• Web UI Test: Start Web server and keep running for complete Web functionality testing

🆕 Version History

📋 Complete Version History: RELEASE_NOTES/CHANGELOG.en.md

Latest Version Highlights (v2.4.0)

• 🤖 AI Conversation End Detection: Automatically detects AI conversation ending phrases and triggers MCP feedback
• ⏱️ Extended Timeout: Default timeout increased by 40% (from 600s to 840s) for better user experience
• 🎯 Auto Trigger Control: New MCP_AUTO_TRIGGER environment variable to control automatic triggering
• 🔧 Enhanced Package Name: Released as mcp-feedback-enhanced-tuning-mbpr to avoid conflicts
• 📋 Improved Documentation: Updated configuration examples and usage guides

🐛 Common Issues

🌐 SSH Remote Environment Issues

Q: Browser cannot launch in SSH Remote environment A: This is normal behavior. SSH Remote environments have no graphical interface, requiring manual opening in local browser. For detailed solutions, see: SSH Remote Environment Usage Guide

Q: Why am I not receiving new MCP feedback? A: There might be a WebSocket connection issue. Solution: Simply refresh the browser page.

Q: Why isn't MCP being called? A: Please confirm the MCP tool status shows green light. Solution: Toggle the MCP tool on/off repeatedly, wait a few seconds for system reconnection.

Q: Augment cannot start MCP A: Solution: Completely close and restart VS Code or Cursor, then reopen the project.

🔧 General Issues

Q: Getting "Unexpected token 'D'" error A: Debug output interference. Set MCP_DEBUG=false or remove the environment variable.

Q: Chinese character garbled text A: Fixed in v2.0.3. Update to latest version: uvx mcp-feedback-enhanced-tuning-mbpr@latest

Q: Multi-screen window disappearing or positioning errors A: Fixed in v2.1.1. Go to "⚙️ Settings" tab, check "Always show window at primary screen center" to resolve. Especially useful for T-shaped screen arrangements and other complex multi-monitor configurations.

Q: Image upload fails A: Check file size (≤1MB) and format (PNG/JPG/GIF/BMP/WebP).

Q: Web UI won't start A: Set FORCE_WEB=true or check firewall settings.

Q: UV Cache taking up too much disk space A: Due to frequent use of uvx commands, cache may accumulate to tens of GB. Regular cleanup is recommended:

# Check cache size and detailed information
python scripts/cleanup_cache.py --size

# Preview cleanup content (without actually cleaning)
python scripts/cleanup_cache.py --dry-run

# Execute standard cleanup
python scripts/cleanup_cache.py --clean

# Force cleanup (attempts to close related processes, solves Windows file lock issues)
python scripts/cleanup_cache.py --force

# Or use uv command directly
uv cache clean

For detailed instructions, see: Cache Management Guide

Q: AI models cannot parse images A: Various AI models (including Gemini Pro 2.5, Claude, etc.) may have instability in image parsing, sometimes correctly identifying and sometimes unable to parse uploaded image content. This is a known limitation of AI visual understanding technology. Recommendations:

1. Ensure good image quality (high contrast, clear text)
2. Try uploading multiple times, retries usually succeed
3. If parsing continues to fail, try adjusting image size or format

🙏 Acknowledgments

🌟 Support Original Author

Fábio Ferreira - X @fabiomlferreira Original Project: noopstudios/interactive-feedback-mcp

If you find this useful, please:

• ⭐ Star the original project
• 📱 Follow the original author

Design Inspiration

sanshao85 - mcp-feedback-collector

Contributors

penn201500 - GitHub @penn201500

• 🎯 Auto-focus input box feature (PR #39)

Community Support

• Discord: https://discord.gg/Gur2V67
• Issues: GitHub Issues

📄 License

MIT License - see LICENSE file for details

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