mcp-feedback-enhanced
Enhanced MCP server supporting user feedback and command execution, ideal for AI-assisted development.
- Type
- MCP
- Transport
- stdio
- Open source
- Yes
- GitHub Stars
- ★ 3.8k
- Source
- mcp-github
Overview
This is an enhanced MCP server designed to enable interactive user feedback and command execution in AI-assisted development. It offers two interface options: Web UI and desktop application, supports intelligent environment detection and cross-platform compatibility. By guiding the AI to confirm with users instead of making speculative actions, it integrates multiple tool calls into a single feedback-driven request, significantly reducing platform costs and improving development efficiency. This capability is well-suited for AI development scenarios requiring frequent user interaction.
Capabilities
- ▪Dual interface support (Web UI and desktop app)
- ▪Intelligent environment detection
- ▪Cross-platform compatibility
- ▪Real-time feedback
- ▪Session tracking
- ▪Automatic command execution
Use cases
Setup
npm install mcp-feedback-enhanced
This information was compiled by AI from public sources and may contain inaccuracies — please refer to the source.
FAQ
Automatically starts the desktop application or browser interface based on configuration.
How do I start the desktop application?
Supports Windows, macOS, Linux, and other platforms.
Which platforms are supported?
Related skills
mantis
Provides security review capabilities for AI coding agents, automatically discovering, reproducing, and fixing vulnerabilities.
sast-skills
Transform your AI coding assistant into a SAST scanner to automatically detect vulnerabilities in code.
Lightswind-UI-Library
AI-native CLI-first React component library with MCP Server support.
scientific-agent-skills
Transform any AI agent into a scientific assistant with 147 ready-to-use research skills.
susi_alexa_skill
A skill that enables question-and-answer interactions between Alexa and Susi AI.
claude-context
Provides code search capabilities for Claude Code, turning the entire codebase into context.