개요

medusa-mcp는 ** Model Context Protocol (MCP) 서버** Medusa JavaScript SDK와 통합하도록 설계되었습니다. Medusa의 데이터 모델과 상호 작용을 위한 확장 가능한 백엔드 레이어를 제공하여 자동화, 관현관, 지능형 서비스 확장을 가능하게 합니다.

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MCP 서버는 무엇입니까?

MCP 서버는 모듈식, 확장 가능한 백엔드입니다.

• Enables **실시간 서비스 오케스트라 **
• 지원 ** 표준화 된, 높은 처리 통신 **
• AI/automation 도구와 실제 시스템 사이의 ** 브리지 역할을 합니다 **

이 서버는 AI, IoT 및 엔터프라이즈 소프트웨어와 같은 영역에서 JSON-RPC와 같은 표준화 된 프로토콜을 사용하여 다양한 서비스 및 자동화 작업을 연결하는 데 사용됩니다.

☸ 열쇠 특징

• Modular Architecture – 유연성을 위한 Composable 서비스
• ** 고효율 ** - 속도 및 스케일 최적화
• Extensible Design – 새로운 기능을 쉽게 추가
• Cross-Environment Deployment – 클라우드, 온프레미스, 또는 하이브리드
• AI-Ready Interfaces – LLM 및 도구 통합

AI AI 시스템의 역할

MCP 서버는 AI 대리인을 허용합니다:

• API, 파일, 데이터베이스에서 실시간 데이터 액세스

medusa-mcp

Overview

medusa-mcp is a Model Context Protocol (MCP) server designed for integration with the Medusa JavaScript SDK. It provides a scalable backend layer for managing and interacting with Medusa’s data models, enabling automation, orchestration, and intelligent service extensions.

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🧩 What is an MCP Server?

An MCP server is a modular, extensible backend that:

• Enables real-time service orchestration
• Supports standardized, high-throughput communication
• Acts as a bridge between AI/automation tools and real-world systems

These servers are used in areas like AI, IoT, and enterprise software to connect various services and automate tasks using standardized protocols like JSON-RPC.

🔑 Key Features

• Modular Architecture – Composable services for flexibility
• High Efficiency – Optimized for speed and scale
• Extensible Design – Add new capabilities easily
• Cross-Environment Deployment – Cloud, on-prem, or hybrid
• AI-Ready Interfaces – Integrate LLMs and tools seamlessly

🧠 Role in AI Systems

MCP servers allow AI agents to:

• Access real-time data from APIs, files, or databases
• Automate business processes (e.g., order fulfillment, pricing updates)
• Interact with external services in a secure and controlled way

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🚀 Medusa JS + MCP

Using medusa-mcp, Medusa JS can:

• Automate workflows (e.g., inventory or pricing adjustments)
• Connect with external tools (email, analytics, etc.)
• Use AI agents to analyze trends and trigger actions
• Enable scalable, modular architecture for commerce platforms

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✨ Features

• ✅ Model Context Protocol (MCP) support
• 📈 Scalable infrastructure
• 🧱 Extensible plugin architecture
• 🔗 Integrated with Medusa JS SDK

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🛠️ Installation

Clone the repository and install dependencies:

npm install

Build the project:

npm run build

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▶️ Usage

Start the server:

npm start

Test using the MCP Inspector:

npx @modelcontextprotocol/inspector ./dist/index.js

Note: Restart the Inspector and your browser after each rebuild.

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🛠️ Generating a Claude Skill from this MCP server

You can convert this MCP server into a Claude Skill using the mcp-to-skill.py script from the mcp-to-skill-converter project, which is included in this repo as mcp-to-skill.py.

1. Build the MCP server (so the command in the config works):

   npm run build
   

2. Ensure Python and the mcp package are available:

   pip install mcp
   

3. Generate a Skill for this server using the provided mcp-to-skill.json config: