# gl-mcp-feedback

> Use this tool when you need to streamline AI development and user confirmation processes, as it provides an interactive feedback MCP server with a Web UI to enhance efficiency and reduce platform costs. It solves problems related to manual confirmation and feedback loops, automating the interaction between AI models and users. Ideal for use cases requiring iterative development and user validation, it takes in AI model outputs and user inputs, generating confirmed results as output.

Canonical page: https://skillsregistry.net/skills/teacat99-gl-mcp-feedback  
JSON: https://api.skillsregistry.net/v1/skills/teacat99-gl-mcp-feedback

## Description

提供交互式反馈MCP服务器，通过Web UI实现AI与用户的确认流程，提高开发效率并节省平台成本。

## Trust

- **Trust score (0–1):** 0.66
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/tm6epnrk8y)
- **Repository:** <https://github.com/teacat99/gl-mcp-feedback>

## 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": "teacat99-gl-mcp-feedback"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/teacat99-gl-mcp-feedback` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/teacat99-gl-mcp-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