# mcp-review

> mcp-review — apatureai-mcp-review. Use this tool when you need to review and refine web previews in a collaborative design environment. It solves problems of iterative design refinement by providing structured findings and suggested fixes for submitted preview URLs. The tool accepts preview URLs as input and outputs actionable feedback, making it ideal for in-loop design review and improvement workflows.

Canonical page: https://skillsregistry.net/skills/apatureai-mcp-review  
JSON: https://api.skillsregistry.net/v1/skills/apatureai-mcp-review

## Description

An MCP server for in-loop design review of web previews. It enables agents to submit a preview URL, receive structured findings with suggested fixes, and recheck after applying changes, while never editing code itself.

## Trust

- **Trust score (0–1):** 0.66
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/noeruz3l9a)
- **Repository:** <https://github.com/apatureai/bastion>

## 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": "apatureai-mcp-review"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/apatureai-mcp-review` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/apatureai-mcp-review/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