A
securityA
licenseA
qualityEnables interaction with Shopify store data using the GraphQL API, supporting product, customer, and order management with comprehensive error handling.
Last updated -
51
14
MIT License
Turbify Store MCP Server
A Model Context Protocol (MCP) server for managing Turbify Store catalogs. This server provides tools to create, update, delete, and search catalog items through the Turbify Store Catalog API.
Features
Item Management: Create, update, and delete catalog items
Search: Search through your catalog using keywords
Configuration: View and manage store settings
Error Handling: Comprehensive error handling and reporting
Documentation: Built-in API documentation via MCP resources
Installation
Clone this repository:
git clone <your-repo-url>
cd turbify-mcp
Initialize with uv (recommended):
uv init .
uv add fastmcp pydantic requests urllib3
Or install with pip:
pip install -e .
Configuration
Set the following environment variables:
export TURBIFY_STORE_ID="your_store_id"
export TURBIFY_CONTRACT_TOKEN="your_contract_token"
Or create a .env file:
TURBIFY_STORE_ID=your_store_id
TURBIFY_CONTRACT_TOKEN=your_contract_token
Usage
Running the Server
python src/turbify_mcp/server.py
Or if installed:
turbify-mcp
Using MCP Inspector
mcp-inspector "python run_server.py"
Available Tools
create_catalog_item
Create a new item in your catalog:
create_catalog_item(
item_id="ITEM123",
name="Sample Product",
table_id="TABLE1",
price=29.99,
sale_price=24.99,
orderable="yes",
taxable="yes"
)
update_catalog_item
Update an existing item:
update_catalog_item(
item_id="ITEM123",
name="Updated Product Name",
price=34.99
)
delete_catalog_item
Delete an item:
delete_catalog_item(item_id="ITEM123")
search_catalog_items
Search for items:
search_catalog_items(
keyword="shirt",
start_index=1,
end_index=50
)
get_store_config
Get current configuration:
get_store_config()
MCP Integration
This server can be used with any MCP-compatible client, such as:
Claude Desktop
Custom MCP clients
Development tools that support MCP
Claude Desktop Configuration
Add to your Claude Desktop config:
{
"mcpServers": {
"turbify-store": {
"command": "python",
"args": ["path/to/turbify-store-mcp/src/turbify_store_mcp/server.py"],
"env": {
"TURBIFY_STORE_ID": "your_store_id",
"TURBIFY_CONTRACT_TOKEN": "your_contract_token"
}
}
}
}
API Response Format
All tools return JSON responses with the following structure:
Success Response
{
"status": "success",
"messages": [
{
"code": "SUCCESS",
"message": "Operation completed successfully"
}
],
"items": [...], // For search operations
"item_ids": [...] // For some operations
}
Error Response
{
"status": "error",
"errors": [
{
"code": "ERROR_CODE",
"message": "Error description"
}
]
}
Development
Setting up for development:
# Install with development dependencies
uv add --dev pytest pytest-asyncio black mypy
# Run tests
uv run pytest
# Format code
uv run black .
# Type checking
uv run mypy src/
Project Structure
turbify-mcp/
├── src/
│ └── turbify_mcp/
│ ├── __init__.py
│ └── server.py
├── tests/
├── pyproject.toml
├── README.md
└── .env
Requirements
Python 3.8+
Turbify Store API credentials
FastMCP
Pydantic v2
Requests
Limitations
Maximum 1000 items per search query (Turbify API limit)
Rate limiting as per Turbify Store API terms
XML-based API (handled internally)
Contributing
Fork the repository
Create a feature branch
Make your changes
Add tests if applicable
Submit a pull request
License
[Add your license information here]
Support
For issues related to:
This MCP server: Create an issue in this repository
Turbify Store API: Consult Turbify Store API documentation
MCP protocol: Check the Model Context Protocol specification
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