# Interactive Feedback

> Use this tool when you need to integrate human feedback into AI workflows, enabling users to validate, approve, or provide additional input during task execution. It solves problems in code review, deployment confirmation, and iterative development by providing a web interface for real-time feedback and console output. The tool accepts user input through a browser-based UI and returns structured JSON data to the AI assistant, making it ideal for human-in-the-loop workflows.

Canonical page: https://skillsregistry.net/skills/interactive-feedback  
JSON: https://api.skillsregistry.net/v1/skills/interactive-feedback

## Description

Interactive Feedback MCP provides a Node.js-based server that enables AI assistants to request human feedback during task execution through a modern web interface. The implementation launches a browser-based UI where users can run commands, view console output in real-time via WebSocket connections, and provide interactive feedback that gets returned to the AI assistant as structured JSON data. Built with Express, WebSocket support, and cross-platform process management, it's designed for human-in-the-loop workflows where AI assistants need user validation, approval, or additional input before proceeding with tasks, making it valuable for code review processes, deployment confirmations, and iterative development scenarios.

## Trust

- **Trust score (0–1):** 0.44
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** devops-ci
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/interactive-feedback)
- **Repository:** <https://github.com/zivhdinfo/interactive-feedback-mcp-nodejs>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "interactive-feedback"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/interactive-feedback` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/interactive-feedback/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt