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MCP Feedback Enhanced

CommunityPopular
Minidoracat

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.

PublisherMinidoracat
Repositorymcp-feedback-enhanced
LanguageJavaScript
Forks
350
Stars
3.8K
Available tools
0
Transport typestdio
Categories
LicenseNOASSERTION
Links
  • Connect tools to AI workflows

    MCP Feedback Enhanced exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    3.8K stars and 350 forks from the linked repository.

MCP Feedback Enhanced

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

Original Author: Fábio Ferreira | Original ProjectEnhanced Fork: Minidoracat UI Design Reference: sanshao85/mcp-feedback-collector

🎯 Core Concept

This is an MCP server that establishes feedback-oriented development workflows, providing Web UI and Desktop Application dual interface options, perfectly adapting to local, SSH Remote environments, 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.

🌐 Dual Interface Architecture Advantages:

  • 🖥️ Desktop Application: Native cross-platform desktop experience, supporting Windows, macOS, Linux
  • 🌐 Web UI: No GUI dependencies required, suitable for remote and WSL environments
  • 🔧 Flexible Deployment: Choose the most suitable interface mode based on environment requirements
  • 📦 Unified Functionality: Both interfaces provide exactly the same functional experience

🖥️ Desktop Application: v2.5.0 introduces cross-platform desktop application support based on Tauri framework, supporting Windows, macOS, and Linux platforms with native desktop experience.

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

🔄 Workflow

  1. AI Callmcp-feedback-enhanced tool
  2. Interface Launch → Auto-open desktop application or browser interface (based on configuration)
  3. Smart Interaction → Prompt selection, text input, image upload, auto-submit
  4. Real-time Feedback → WebSocket connection delivers information to AI instantly
  5. Session Tracking → Auto-record session history and statistics
  6. Process Continuation → AI adjusts behavior or ends task based on feedback

🌟 Key Features

🖥️ Dual Interface Support

  • Desktop Application: Cross-platform native application based on Tauri, supporting Windows, macOS, Linux
  • Web UI Interface: Lightweight browser interface suitable for remote and WSL environments
  • Automatic Environment Detection: Intelligently recognizes SSH Remote, WSL and other special environments
  • Unified Feature Experience: Both interfaces provide exactly the same functionality

📝 Smart Workflow

  • Prompt Management: CRUD operations for common prompts, usage statistics, intelligent sorting
  • Auto-Timed Submit: 1-86400 second flexible timer, supports pause, resume, cancel with new pause/resume button controls
  • Auto Command Execution (v2.6.0): Automatically execute preset commands after creating new sessions or commits for improved development efficiency
  • Session Management & Tracking: Local file storage, privacy controls, history export (supports JSON, CSV, Markdown formats), real-time statistics, flexible timeout settings
  • Connection Monitoring: WebSocket status monitoring, auto-reconnection, quality indicators
  • AI Work Summary Markdown Display: Support for rich Markdown syntax rendering including headers, bold text, code blocks, lists, links and other formats for enhanced content readability

🎨 Modern Experience

  • Responsive Design: Adapts to different screen sizes, modular JavaScript architecture
  • Audio Notifications: Built-in multiple sound effects, custom audio upload support, volume control
  • System Notifications (v2.6.0): System-level real-time alerts for important events (like auto-commit, session timeout)
  • Smart Memory: Input box height memory, one-click copy, persistent settings
  • Multi-language Support: Traditional Chinese, English, Simplified Chinese, instant switching

🖼️ Images & Media

  • Full Format Support: PNG, JPG, JPEG, GIF, BMP, WebP
  • Convenient Upload: Drag & drop files, clipboard paste (Ctrl+V)
  • Unlimited Processing: Support for any size images, automatic intelligent processing

🌐 Interface Preview

Web UI Interface (v2.5.0 - Desktop Application Support)

Web UI Interface - Supports desktop application and Web interface, providing prompt management, auto-submit, session tracking and other smart features

Desktop Application Interface (v2.5.0 New Feature)

Desktop Application - Native cross-platform desktop application based on Tauri framework, supporting Windows, macOS, Linux with exactly the same functionality as Web UI

Shortcut Support

  • Ctrl+Enter(Windows/Linux)/ Cmd+Enter(macOS):Submit feedback (both main keyboard and numeric keypad supported)
  • Ctrl+V(Windows/Linux)/ Cmd+V(macOS):Direct paste clipboard images
  • Ctrl+I(Windows/Linux)/ Cmd+I(macOS):Quick focus input box (Thanks @penn201500)

🚀 Quick Start

1. Installation & Testing

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

2. Configure MCP

Basic Configuration (suitable for most users):

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

Advanced Configuration (requires custom environment):

json
{
  "mcpServers": {
    "mcp-feedback-enhanced": {
      "command": "uvx",
      "args": ["mcp-feedback-enhanced@latest"],
      "timeout": 600,
      "env": {
        "MCP_DEBUG": "false",
        "MCP_WEB_HOST": "127.0.0.1",
        "MCP_WEB_PORT": "8765",
        "MCP_LANGUAGE": "en"
      },
      "autoApprove": ["interactive_feedback"]
    }
  }
}

Desktop Application Configuration (v2.5.0 new feature - using native desktop application):

json
{
  "mcpServers": {
    "mcp-feedback-enhanced": {
      "command": "uvx",
      "args": ["mcp-feedback-enhanced@latest"],
      "timeout": 600,
      "env": {
        "MCP_DESKTOP_MODE": "true",
        "MCP_WEB_HOST": "127.0.0.1",
        "MCP_WEB_PORT": "8765",
        "MCP_DEBUG": "false"
      },
      "autoApprove": ["interactive_feedback"]
    }
  }
}

Configuration File Examples:

3. Prompt Engineering Setup

For optimal results, add the following rules to your AI assistant:

# MCP Interactive Feedback Rules

follow mcp-feedback-enhanced instructions

⚙️ Advanced Settings

Environment Variables

VariablePurposeValuesDefault
MCP_DEBUGDebug modetrue/falsefalse
MCP_WEB_HOSTWeb UI host bindingIP address or hostname127.0.0.1
MCP_WEB_PORTWeb UI port1024-655358765
MCP_DESKTOP_MODEDesktop application modetrue/falsefalse
MCP_LANGUAGEForce UI languagezh-TW/zh-CN/enAuto-detect

MCP_WEB_HOST Explanation:

  • 127.0.0.1 (default): Local access only, higher security
  • 0.0.0.0: Allow remote access, suitable for SSH remote development environments

MCP_LANGUAGE Explanation:

  • Used to force the interface language, overriding automatic system detection
  • Supported language codes:
    • zh-TW: Traditional Chinese
    • zh-CN: Simplified Chinese
    • en: English
  • Language detection priority:
    1. User-saved language settings in the interface (highest priority)
    2. MCP_LANGUAGE environment variable
    3. System environment variables (LANG, LC_ALL, etc.)
    4. System default language
    5. Fallback to default language (Traditional Chinese)

Testing Options

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

# Interface testing
uvx mcp-feedback-enhanced@latest test --web    # Test Web UI (auto continuous running)
uvx mcp-feedback-enhanced@latest test --desktop # Test desktop application (v2.5.0 new feature)

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

# Specify language for testing
MCP_LANGUAGE=en uvx mcp-feedback-enhanced@latest test --web    # Force English interface
MCP_LANGUAGE=zh-TW uvx mcp-feedback-enhanced@latest test --web  # Force Traditional Chinese
MCP_LANGUAGE=zh-CN uvx mcp-feedback-enhanced@latest test --web  # Force Simplified Chinese

Developer Installation

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

Local Testing Methods

bash
# Functional testing
make test-func                                           # Standard functional testing
make test-web                                            # Web UI testing (continuous running)
make test-desktop-func                                   # Desktop application functional testing

# Or use direct commands
uv run python -m mcp_feedback_enhanced test              # Standard functional testing
uvx --no-cache --with-editable . mcp-feedback-enhanced test --web   # Web UI testing (continuous running)
uvx --no-cache --with-editable . mcp-feedback-enhanced test --desktop # Desktop application testing

# Desktop application build (v2.5.0 new feature)
make build-desktop                                       # Build desktop application (debug mode)
make build-desktop-release                               # Build desktop application (release mode)
make test-desktop                                        # Test desktop application
make clean-desktop                                       # Clean desktop build artifacts

# Unit testing
make test                                                # Run all unit tests
make test-fast                                          # Fast testing (skip slow tests)
make test-cov                                           # Test and generate coverage report

# Code quality checks
make check                                              # Complete code quality check
make quick-check                                        # Quick check and auto-fix

Testing Descriptions

  • Functional Testing: Test complete MCP tool functionality workflow
  • Unit Testing: Test individual module functionality
  • Coverage Testing: Generate HTML coverage report to htmlcov/ directory
  • Quality Checks: Include linting, formatting, type checking

🆕 Version History

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

Latest Version Highlights (v2.6.0)

  • 🚀 Auto Command Execution: Automatically execute preset commands after creating new sessions or commits, improving workflow efficiency
  • 📊 Session Export Feature: Support exporting session records to multiple formats for easy sharing and archiving
  • ⏸️ Auto-commit Control: Added pause and resume buttons for better control over auto-commit timing
  • 🔔 System Notifications: System-level notifications for important events with real-time alerts
  • ⏱️ Session Timeout Optimization: Redesigned session management with more flexible configuration options
  • 🌏 I18n Enhancement: Refactored internationalization architecture with full multilingual support for notifications
  • 🎨 UI Simplification: Significantly simplified user interface for improved user experience

🐛 Common Issues

🌐 SSH Remote Environment Issues

Q: Browser cannot launch or access in SSH Remote environment A: Two solutions available:

Solution 1: Environment Variable Setting (v2.5.5 Recommended) Set "MCP_WEB_HOST": "0.0.0.0" in MCP configuration to allow remote access:

json
{
  "mcpServers": {
    "mcp-feedback-enhanced": {
      "command": "uvx",
      "args": ["mcp-feedback-enhanced@latest"],
      "timeout": 600,
      "env": {
        "MCP_WEB_HOST": "0.0.0.0",
        "MCP_WEB_PORT": "8765"
      },
      "autoApprove": ["interactive_feedback"]
    }
  }
}

Then open in local browser: http://[remote-host-IP]:8765

Solution 2: SSH Port Forwarding (Traditional Method)

  1. Use default configuration (MCP_WEB_HOST: 127.0.0.1)
  2. Set up SSH port forwarding:
    • VS Code Remote SSH: Press Ctrl+Shift+P → "Forward a Port" → Enter 8765
    • Cursor SSH Remote: Manually add port forwarding rule (port 8765)
  3. Open in local browser: http://localhost:8765

For detailed solutions, refer to: SSH Remote Environment Usage Guide

Q: Why am I not receiving new MCP feedback? A: Likely a WebSocket connection issue. Solution: Directly refresh the browser page.

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

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

🔧 General Issues

Q: How to use desktop application? A: v2.5.0 introduces cross-platform desktop application support. Set "MCP_DESKTOP_MODE": "true" in MCP configuration to enable:

json
{
  "mcpServers": {
    "mcp-feedback-enhanced": {
      "command": "uvx",
      "args": ["mcp-feedback-enhanced@latest"],
      "timeout": 600,
      "env": {
        "MCP_DESKTOP_MODE": "true",
        "MCP_WEB_PORT": "8765"
      },
      "autoApprove": ["interactive_feedback"]
    }
  }
}

Configuration File Example: examples/mcp-config-desktop.json

Q: How to use legacy PyQt6 GUI interface? A: v2.4.0 completely removed PyQt6 GUI dependencies. To use legacy GUI, specify v2.3.0 or earlier: uvx mcp-feedback-enhanced@2.3.0 Note: Legacy versions don't include new features (prompt management, auto-submit, session management, desktop application, etc.).

Q: "Unexpected token 'D'" error appears 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@latest

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

Q: Image upload failure A: Check file format (PNG/JPG/JPEG/GIF/BMP/WebP). System supports any size image files.

Q: Web UI cannot start A: Check firewall settings or try using different ports.

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

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

# Preview cleanup content (no actual cleanup)
python scripts/cleanup_cache.py --dry-run

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

# Force cleanup (attempts to close related programs, solving Windows file occupation issues)
python scripts/cleanup_cache.py --force

# Or directly use uv command
uv cache clean

For detailed instructions, refer to: 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 recognizing 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 it useful, please:

Design Inspiration

sanshao85 - mcp-feedback-collector

Contributors

penn201500 - GitHub @penn201500

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

leo108 - GitHub @leo108

  • 🌐 SSH Remote Development Support (MCP_WEB_HOST environment variable) (PR #113)

Alsan - GitHub @Alsan

  • 🍎 macOS PyO3 Compilation Configuration Support (PR #93)

fireinice - GitHub @fireinice

  • 📝 Tool Documentation Optimization (LLM instructions moved to docstring) (PR #105)

Community Support

📄 License

MIT License - See LICENSE file for details

📈 Star History

Star History Chart


🌟 Welcome to Star and share with more developers!

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "mcp-feedback-enhanced": {
      "command": "uvx",
      "args": [
        "mcp-feedback-enhanced@latest"
      ]
    }
  }
}

Use MCP Feedback Enhanced MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once MCP Feedback Enhanced is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add MCP Feedback Enhanced as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the MCP Feedback Enhanced MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "mcp-feedback-enhanced": {
      "command": "npx",
      "args": [
        "-y",
        "null"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the MCP Feedback Enhanced MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the MCP Feedback Enhanced MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use MCP Feedback Enhanced to help me with this task?
MCP Feedback Enhanced
Sure. I read it.
Here is what I found using MCP Feedback Enhanced.

Frequently asked questions

What is the MCP Feedback Enhanced MCP server used for?

MCP Feedback Enhanced is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use MCP Feedback Enhanced MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use MCP Feedback Enhanced with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use MCP Feedback Enhanced MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With MCP Feedback Enhanced connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect MCP Feedback Enhanced MCP to TypingMind?

MCP Feedback Enhanced runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does MCP Feedback Enhanced MCP provide in TypingMind?

MCP Feedback Enhanced exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use MCP Feedback Enhanced MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If MCP Feedback Enhanced requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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