# MAGI MCP Server

> Use this tool when you need to orchestrate code reviews using a multi-agent system, solving problems of collaborative review and feedback management. The MAGI MCP Server implements the Model Context Protocol, taking in code review inputs and outputting orchestrated feedback through its interface with Melchior, Balthasar, and Casper agents. Ideal for use in software development teams requiring structured and automated code review processes.

Canonical page: https://skillsregistry.net/skills/miki-hoshizaki-mcp-magi  
JSON: https://api.skillsregistry.net/v1/skills/miki-hoshizaki-mcp-magi

## Description

A server that implements the Model Context Protocol (MCP) for orchestrating code reviews using a multi-agent system with Melchior, Balthasar, and Casper agents.

## Trust

- **Trust score (0–1):** 0.94
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/naunhpm1jr)
- **Repository:** <https://github.com/Miki-Hoshizaki/mcp-magi>

## 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": "miki-hoshizaki-mcp-magi"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/miki-hoshizaki-mcp-magi` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/miki-hoshizaki-mcp-magi/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