Shopify MCP Server

Shopify MCP Server

Enables management of Shopify orders through the Admin REST API, allowing users to create new orders and retrieve order status details. It supports both local and remote access via SSE and STDIO transports for integration with MCP clients like Claude Desktop.

Category
Visit Server

README

Shopify MCP Server

A Model Context Protocol (MCP) server for Shopify order management using the official MCP Python SDK.

Features

  • āœ… MCP-Compliant: Follows official MCP specification
  • šŸ› ļø Two Tools: Create orders and check order status via Shopify Admin REST API
  • 🌐 Remote Access: SSE transport for cloud deployment
  • šŸ”’ Secure: Environment-based credential management

Available Tools

1. create_order

Create new Shopify orders with line items and customer information.

Parameters:

  • line_items (array, required): Product items to order
  • customer_email (string, optional): Customer email
  • financial_status (string, optional): Payment status (default: "pending")
  • test (boolean, optional): Create as test order (default: true)

2. get_order_status

Retrieve complete order details by order ID.

Parameters:

  • order_id (integer, required): Shopify order ID

Quick Start

Prerequisites

  • Python 3.10 or higher
  • Shopify Admin API access token
  • Shopify store URL

Local Setup

# Clone the repository
cd mcp-server

# Create and activate virtual environment (recommended)
python -m venv mcpserver
mcpserver\Scripts\activate  # Windows
# source mcpserver/bin/activate  # macOS/Linux

# Install dependencies
pip install -r requirements.txt

# Configure environment variables
# Create .env file with:
SHOPIFY_ADMIN_API_BASE_URL=https://your-store.myshopify.com/admin/api/2025-07
SHOPIFY_ACCESS_TOKEN=your_access_token_here
USE_DUMMY_RESPONSES=true  # Optional: returns mock data when API fails (for testing)

# Run the server
python shopify_mcp_server.py

Testing Mode (Dummy Responses)

For development and testing without valid Shopify credentials, enable dummy response mode:

# In .env file
USE_DUMMY_RESPONSES=true

When enabled:

  • āœ… API errors return realistic mock data instead of error messages
  • āœ… Test tools without valid Shopify store credentials
  • āœ… See what successful responses look like
  • āœ… All responses include "dummy_mode": true flag

Demo:

python demo_dummy_responses.py

Example dummy response:

{
  "success": true,
  "dummy_mode": true,
  "order_id": 9999999999,
  "order_number": 1001,
  "financial_status": "paid",
  "total_price": "79.97",
  "note": "This is a dummy response for testing purposes"
}

Disable for production:

USE_DUMMY_RESPONSES=false  # or remove the variable entirely

Usage with MCP Clients

Claude Desktop Integration

Add to your Claude Desktop configuration file:

Windows: %APPDATA%\Claude\claude_desktop_config.json
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "shopify": {
      "command": "python",
      "args": ["C:\\path\\to\\mcp-server\\shopify_mcp_server.py"],
      "env": {
        "SHOPIFY_ADMIN_API_BASE_URL": "https://your-store.myshopify.com/admin/api/2025-07",
        "SHOPIFY_ACCESS_TOKEN": "your_access_token_here"
      }
    }
  }
}

Restart Claude Desktop, and you'll see the Shopify tools available.

MCP Inspector (Testing)

Test your server with the official MCP Inspector:

npx @modelcontextprotocol/inspector python shopify_mcp_server.py

This opens a web interface to test tool discovery and execution.

Remote Deployment

The server uses SSE (Server-Sent Events) transport for remote access, making it compatible with cloud platforms.

Railway Deployment

  1. Fork/Clone this repository

  2. Connect to Railway:

    • Go to Railway.app
    • Click "New Project" → "Deploy from GitHub repo"
    • Select this repository
  3. Set Environment Variables in Railway dashboard:

    SHOPIFY_ADMIN_API_BASE_URL=https://your-store.myshopify.com/admin/api/2025-07
    SHOPIFY_ACCESS_TOKEN=your_access_token_here
    
  4. Deploy: Railway auto-deploys from Procfile

Your MCP server will be available at: https://your-app.up.railway.app

Render Deployment

  1. Connect GitHub repo to Render
  2. Create new Web Service
  3. Set environment variables
  4. Set start command: python shopify_mcp_server.py

Other Platforms (Fly.io, Heroku, etc.)

The server works on any platform supporting Python web services. Use the start command:

python shopify_mcp_server.py

Transport Options

The server supports two transport modes (configured in code):

# SSE Transport (remote access, default)
mcp.run(transport="sse")

# STDIO Transport (local only, for Claude Desktop)
mcp.run(transport="stdio")

Current configuration: SSE (remote deployment)

Environment Variables

Variable Description Example
SHOPIFY_ADMIN_API_BASE_URL Shopify Admin API endpoint https://store.myshopify.com/admin/api/2025-07
SHOPIFY_ACCESS_TOKEN Admin API access token shpat_xxxxx
USE_DUMMY_RESPONSES Enable mock responses for testing (optional) true or false (default: false)

Security Best Practices

āš ļø Important Security Notes:

  • Never commit .env files to version control (already in .gitignore)
  • Use environment variables on hosting platforms
  • Rotate access tokens regularly
  • Enable HTTPS in production (automatic on Railway/Render)
  • Restrict API scopes to minimum required permissions

Troubleshooting

"SHOPIFY_ACCESS_TOKEN not set"

  • Verify .env file exists and contains the token
  • Check environment variables in your deployment platform

"Order not found" (404)

  • Verify the order ID is correct (use numeric ID, not order number)
  • Check API access token has permission to read orders

Tools not appearing in Claude Desktop

  • Verify configuration file path is correct
  • Check Python path in the command field
  • Restart Claude Desktop after config changes
  • Check Claude Desktop logs for errors

Development

Project Structure

mcp-server/
ā”œā”€ā”€ shopify_mcp_server.py   # Main MCP server
ā”œā”€ā”€ requirements.txt         # Python dependencies
ā”œā”€ā”€ .env                     # Local environment variables (gitignored)
ā”œā”€ā”€ Procfile                # Railway/Heroku deployment
└── README.md               # This file

Testing

Use MCP Inspector for development testing:

npx @modelcontextprotocol/inspector python shopify_mcp_server.py

Resources

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured