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medusa-mcp

MCP.Pizza Chef: SGFGOV

medusa-mcp is an MCP server designed to integrate with the Medusa JavaScript SDK, providing a scalable backend for managing Medusa data models. It enables real-time service orchestration, high-throughput communication, and acts as a bridge between AI tools and Medusa's commerce platform. Its modular, extensible architecture supports flexible deployment across cloud and on-prem environments, optimized for speed and scalability.

Use This MCP server To

Automate e-commerce workflows using Medusa data models Orchestrate real-time inventory and order management Integrate AI-driven automation with Medusa backend Extend Medusa services with custom MCP modules Enable scalable backend communication for Medusa apps Bridge AI tools with Medusa commerce platform APIs

README

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.


🧩 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.

πŸ”‘ 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


πŸš€ 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

✨ Features

  • βœ… Model Context Protocol (MCP) support
  • πŸ“ˆ Scalable infrastructure
  • 🧱 Extensible plugin architecture
  • πŸ”— Integrated with Medusa JS SDK

πŸ› οΈ Installation

Clone the repository and install dependencies:

npm install

Build the project:

npm run build

▢️ 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.


🌍 Environment Variables

Variable Description
MEDUSA_BACKEND_URL Your Medusa backend URL
PUBLISHABLE_KEY Your Medusa publishable API key
MEDUSA_USERNAME Medusa admin username (for admin)
MEDUSA_PASSWORD Medusa admin password (for admin)

Server runs at: http://localhost:3000


🧠 Architecture Diagram

Here's how the medusa-mcp server fits into a typical setup with Medusa JS and external systems:


       +-------------------------+
       |     AI Assistant /      |
       |     LLM / Automation    |
       +-----------+-------------+
                   |
                   v
    +--------------+--------------+
    |     MCP Server (medusa-mcp) |
    |-----------------------------|
    | - JSON-RPC Communication    |
    | - AI-Ready Interface        |
    | - Plugin Support            |
    +------+----------------------+
                   |                             
                   +
                   |                                                         
                   v                                                         
         +-------------------+
         | Medusa Backend    |
         | (Products, Orders)|
         +-------------------+
                   |
                   |
                   v
           +--------------+
           | Medusa Store |
           | Frontend     |
           +--------------+
                   |
                   |
                   v
      +-------------------------+
      | External Services / API |
      | (e.g., Payments, Email) |
      +-------------------------+

πŸ§ͺ Customization

To tailor the server to your Medusa setup:

Replace admin.json and store.json with your own OAS definitions for fine-grained control.

  • Replace the OpenAPI schemas in the oas/ folder:
    • admin.json – Admin endpoints
    • store.json – Storefront endpoints

Use the @medusajs/medusa-oas-cli to regenerate these files.

You can also fork this project to build your own custom MCP-powered Medusa integration.


🀝 Contributing

We welcome contributions! Please see our CONTRIBUTING.md guide.


πŸ“„ License

This project is licensed under the MIT License. See the LICENSE file for details.

medusa-mcp FAQ

How do I deploy medusa-mcp in my environment?
medusa-mcp supports cloud and on-prem deployment; follow the GitHub README for setup instructions.
Can I extend medusa-mcp with custom services?
Yes, its modular architecture allows adding new capabilities easily.
What communication protocols does medusa-mcp use?
It uses standardized JSON-RPC for high-throughput, real-time communication.
Is medusa-mcp optimized for performance?
Yes, it is designed for speed and scalability in production environments.
How does medusa-mcp integrate with AI tools?
It acts as a bridge enabling AI and automation tools to interact with Medusa's backend data models.
What environments are supported by medusa-mcp?
It supports deployment across cloud, on-premises, and hybrid environments.
Where can I find documentation for medusa-mcp?
Documentation and usage examples are available on the GitHub repository README.