Minidoracat/mcp-feedback-enhanced

Score: 42.2 Rank #1516

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.

Overview

Minidoracat/mcp-feedback-enhanced is a JavaScript MCP server. 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.

Ranked #1516 out of 25632 indexed tools.

In the top 6% of all indexed tools.

Has 3,615 GitHub stars.

Has 11 contributors.

Ecosystem

JavaScript NOASSERTION

Signal Breakdown

Stars 3,615

Freshness 8mo ago

Issue Health 59%

Contributors 11

Dependents 3

Forks 332

Description Detailed

License NOASSERTION

How to Improve

License low impact

Add an MIT or Apache-2.0 license to signal trust and enable adoption

Freshness high impact

Last commit was 260 days ago — a recent commit would boost your freshness score

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Details

Stars: 3,615
Forks: 332
Open Issues: 79
Closed Issues: 114
Contributors: 11
Dependents: 3
Language: JavaScript
License: NOASSERTION
Last Commit: 8mo ago

Matched Queries

"mcp server""mcp-server"

From the README

# MCP Feedback Enhanced

**🌐 Language / 語言切換:** **English** | [繁體中文](README.zh-TW.md) | [简体中文](README.zh-CN.md)

**Original Author:** [Fábio Ferreira](https://x.com/fabiomlferreira) | [Original Project](https://github.com/noopstudios/interactive-feedback-mcp) ⭐
**Enhanced Fork:** [Minidoracat](https://github.com/Minidoracat)
**UI Design Reference:** [sanshao85/mcp-feedback-collector](https://github.com/sanshao85/mcp-feedback-collector)

## 🎯 Core Concept

This is an [MCP server](https://modelcontextprotocol.io/) 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.

Read full README on GitHub →

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