🛍️ MCP - MCP for Commerce Platforms - Universal E-commerce Cust…
@slavpilus
About 🛍️ MCP - MCP for Commerce Platforms - Universal E-commerce Cust…
MCP for Commerce Platforms
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-slavpilus": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}Tools
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Overview
What is 🛍️ MCP - MCP for Commerce Platforms - Universal E-commerce Customer Support Assistant?
It is a platform-agnostic customer support assistant that connects to any e-commerce platform through pluggable strategies, using the MCP (Model Context Protocol) server and Gradio for the user interface. It is built for developers and support teams who need a single conversational interface to manage orders, returns, and cancellations across multiple e‑commerce backends.
How to use 🛍️ MCP - MCP for Commerce Platforms - Universal E-commerce Customer Support Assistant?
Clone the repository, run the setup script (scripts/setup_dev.sh) or manually create a virtual environment, install dependencies from requirements-dev.txt, copy .env.example to .env and configure it, then run python app.py. The application will be available at http://localhost:7860.
Key features of 🛍️ MCP - MCP for Commerce Platforms - Universal E-commerce Customer Support Assistant
- Order management: track orders, check status, view history
- Returns and refunds: initiate returns, process refunds
- Order cancellations: quick and easy cancellations
- Conversational interface using natural language
- Platform-agnostic, extensible via a strategy pattern
- Auto‑deployment to Hugging Face Spaces
Use cases of 🛍️ MCP - MCP for Commerce Platforms - Universal E-commerce Customer Support Assistant
- A single customer‑facing chat that handles orders from Shopify, Magento, WooCommerce, and other platforms
- Integrating a conversational support assistant into an existing multi‑platform e‑commerce operation
- Rapidly prototyping customer support for a new e‑commerce store using mock data
- Deploying a self‑hosted support assistant to Hugging Face Spaces for internal testing
FAQ from 🛍️ MCP - MCP for Commerce Platforms - Universal E-commerce Customer Support Assistant
Which e‑commerce platforms are supported out of the box?
The README lists MockData, Shopify, Magento, and WooCommerce as platform strategies, and the architecture is extensible to any platform via the strategy interface.
What are the runtime requirements?
Python 3.10 or higher, Git, and a virtual environment tool (venv) are required. All dependencies are listed in requirements-dev.txt.
How do I run the application locally after installation?
Execute python app.py from the project root. The Gradio interface will be available at http://localhost:7860.
How can I deploy the assistant to production?
The project is configured for automatic deployment to Hugging Face Spaces via GitHub Actions on pushes to the main branch, or manual deployment by adding the Spaces remote and pushing.
How do I add support for a new e‑commerce platform?
Create a new strategy class in mcp_server/strategies/ that inherits from EcommerceStrategy, implement the required methods, add tests, and update the strategy factory.
Frequently asked questions
Which e‑commerce platforms are supported out of the box?
The README lists MockData, Shopify, Magento, and WooCommerce as platform strategies, and the architecture is extensible to any platform via the strategy interface.
What are the runtime requirements?
Python 3.10 or higher, Git, and a virtual environment tool (venv) are required. All dependencies are listed in `requirements-dev.txt`.
How do I run the application locally after installation?
Execute `python app.py` from the project root. The Gradio interface will be available at `http://localhost:7860`.
How can I deploy the assistant to production?
The project is configured for automatic deployment to Hugging Face Spaces via GitHub Actions on pushes to the `main` branch, or manual deployment by adding the Spaces remote and pushing.
How do I add support for a new e‑commerce platform?
Create a new strategy class in `mcp_server/strategies/` that inherits from `EcommerceStrategy`, implement the required methods, add tests, and update the strategy factory.
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