# peer-review-mcp

> peer-review-mcp — eyalzh-peer-review-mcp. Use this tool when you need to validate AI-generated content or solicit feedback from more advanced models to improve performance and accuracy. The peer-review-mcp server accepts requests for assistance or feedback and returns constructive input from capable models, facilitating collaborative learning and refinement. Ideal for use cases where AI agents require external evaluation or guidance to enhance their outputs.

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

## Description

This MCP server lets AI agents ask for assistance or feedback from more capable models

## Trust

- **Trust score (0–1):** 0.98
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/eyalzh/peer-review-mcp)

## 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": "eyalzh-peer-review-mcp"
    }
  }
}
```

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