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Shopify

siddhantbajajbysiddhantbajaj
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API Development
Developer Tools
E-commerce Solutions

Connects clients like Claude to Shopify store data via a Model Context Protocol (MCP) server.

The Shopify MCP Server provides a bridge between AI clients, such as Claude, and your Shopify store data. By implementing the Model Context Protocol (MCP), the server exposes tools for retrieving vital information, including product lists and customer details. This allows AI models to interact with and leverage your Shopify data for various applications, such as enhanced customer service, personalized recommendations, and data-driven decision-making.

Key Features

01Configurable limit for product and customer list retrieval
023 GitHub stars
03Retrieves a list of customers from a Shopify store
04Uses environment variables for secure credential management
05Retrieves a list of products from a Shopify store
06Uses Model Context Protocol (MCP) for AI integration

Use Cases

01Integrate Shopify data with AI models like Claude for enhanced analysis
02Build AI-powered tools that leverage product and customer information
03Automate tasks and workflows using Shopify data via MCP

Shopify MCP Server

A Model Context Protocol (MCP) server to connect clients like Claude with Shopify store data. This server exposes tools for retrieving product and customer information from your Shopify store.

Tools

  • get-product-list: Retrieve a list of products from your Shopify store
  • get-customer-list: Retrieve a list of customers from your Shopify store
  • More to come soon

Prerequisites

  • Python 3.12 or higher
  • A Shopify store with API access
  • Shopify API credentials (API Key, Password, and Access Token)

Installation

  1. Clone the repository:
git clone https://github.com/siddhantbajaj/shopify-mcp-server.git
cd shopify-mcp-server
  1. Create and activate a virtual environment using uv:
uv venv
source .venv/bin/activate  # On Unix/MacOS
# or
.venv\Scripts\activate  # On Windows
  1. Install the package:
uv pip install -e .

Configuration

  1. Create a .env file in the root directory with your Shopify credentials:
SHOPIFY_SHOP_URL="your-store.myshopify.com"
SHOPIFY_API_KEY="your_api_key"
SHOPIFY_PASSWORD="your_api_password"
SHOPIFY_ACCESS_TOKEN="your_access_token"

Replace the placeholder values with your actual Shopify API credentials.

Usage

  1. Start the MCP server:
python -m shopify_mcp_server.server
  1. The server exposes two tools:

get-product-list

Retrieves a list of products from your Shopify store.

  • Optional parameter: limit (default: 10) - Maximum number of products to return

get-customer-list

Retrieves a list of customers from your Shopify store.

  • Optional parameter: limit (default: 10) - Maximum number of customers to return

Tool Response Format

Products

Products (showing X):

Title: Product Name
ID: 123456789
Product Type: Type
Vendor: Vendor Name
Status: active
Price: $XX.XX
---

Customers

Customers (showing X):

Name: John Doe
ID: 123456789
Email: john@example.com
Orders Count: X
Total Spent: $XX.XX
---

Development

This project uses:

Security

  • Never commit your .env file to version control
  • Keep your Shopify API credentials secure
  • Use environment variables for sensitive information

License

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

Contributing

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request