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Medusa Mcp

Medusa Mcp

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github.com/SGFGOVBusiness & Marketing70Updated 29w ago

About Medusa Mcp

Medusa Mcp is an MCP server for the Medusa JavaScript SDK, aimed at connecting AI and automation workflows to Medusa commerce data and operations. It includes an extensible plugin architecture and can be customized with Admin and Store OpenAPI schemas.

Key features

  1. 01Medusa JavaScript SDK integration
  2. 02Extensible plugin architecture
  3. 03Admin and Store OpenAPI schema customization
  4. 04Workflow automation for inventory and pricing

Use cases

  1. 01Adjusting inventory through an AI workflow
  2. 02Updating commerce pricing
  3. 03Connecting Medusa operations with external tools

MCP support

It exposes Medusa-backed capabilities to MCP clients through an MCP server. The README describes using it with Medusa JS for data access, workflow automation, and service integrations.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"medusa": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/inspector"
]
}
}
}
Run commandnpx -y @modelcontextprotocol/inspector

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npm@modelcontextprotocol/inspector

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

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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.

🔑 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


🚀 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

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

🛠️ 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.


🛠️ 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:

    python mcp-to-skill.py --mcp-config mcp-to-skill.json --output-dir ./skills/medusa-mcp
    

    This will create:

    • SKILL.md – instructions for Claude
    • executor.py – MCP communication handler
    • mcp-config.json – MCP server configuration
    • package.json – minimal dependencies for the skill
  4. Install the Skill for Claude:

    cd skills/medusa-mcp
    pip install mcp
    cp -r . ~/.claude/skills/medusa-mcp
    

Claude will automatically discover the new Skill on next startup.


🌍 Environment Variables

VariableDescription
MEDUSA_BACKEND_URLYour Medusa backend URL
PUBLISHABLE_KEYYour Medusa publishable API key
MEDUSA_USERNAMEMedusa admin username (for admin)
MEDUSA_PASSWORDMedusa 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) |
      +-------------------------+

🧪 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.


📄 License

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

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.