MAGI Code Review
MAGI MCP Server provides a code review orchestration system that connects AI assistants to a distributed review framework with three specialized agents (Melchior, Balthasar, and Casper). The server establishes WebSocket connections to the MAGI Gateway, submits code for evaluation, and aggregates agent decisions into a final verdict based on majority rule. Built with FastMCP and supporting both SSE and WebSocket transports, it features authentication token generation, detailed logging, and containerization via Docker. This implementation is particularly valuable for developers seeking automated, multi-perspective code quality assessment without leaving their AI assistant interface.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- cloud-infra
- Source
- PulseMCP
- Repository
- github.com/miki-hoshizaki/mcp-magi
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve MAGI Code Review from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.