# mcp-feedback-ultra

> Use this tool when you need to collect and integrate user feedback into AI-assisted development workflows, enabling iterative improvement of AI models through interactive feedback collection via Web UI and desktop apps. It solves problems of limited user input and feedback in AI development, supporting more accurate and effective AI task outcomes. Ideal for use cases requiring human-in-the-loop feedback, such as AI model training and testing.

Canonical page: https://skillsregistry.net/skills/yanghang0210-mcp-feedback-ultra  
JSON: https://api.skillsregistry.net/v1/skills/yanghang0210-mcp-feedback-ultra

## Description

Interactive feedback server for AI-assisted development with Web UI and desktop app support, enabling user feedback collection after AI tasks.

## Trust

- **Trust score (0–1):** 0.25
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** productivity
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ld5hhma4rb)
- **Repository:** <https://github.com/YangHang0210/mcp-feedback-ultra>

## 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": "yanghang0210-mcp-feedback-ultra"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/yanghang0210-mcp-feedback-ultra` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/yanghang0210-mcp-feedback-ultra/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