Enneagora E-commerce MCP Server
Enables customer support across e-commerce platforms by providing order management, product guidance, and account assistance tools through natural language queries.
README
title: Enneagora - E-commerce MCP Server emoji: 🛍️ colorFrom: blue colorTo: purple sdk: gradio sdk_version: 5.33.0 app_file: main.py pinned: true license: mit tags:
- mcp-server-track
- cuustomer support
- commerce
- e-commerce
Enneagora - E-commerce MCP Server
Enneagora is a Universal E-commerce Customer Support Assistant using the Model Context Protocol (MCP) that provides a platform-agnostic solution for customer support across different e-commerce platforms. This comprehensive MCP server can be integrated with Claude Desktop or any MCP-compatible client to handle all aspects of customer inquiries.
🚀 Features
- MCP-Compliant: Dual MCP server implementation using both Gradio and FastMCP with SSE and STDIO transports
- 14 Comprehensive Customer Support Tools:
- Order Management:
get_order_status,cancel_order,process_return,track_package - Support Information:
get_support_info,get_return_policy,get_shipping_info,get_contact_information - Product Guidance:
get_size_guide,get_warranty_information,get_product_care_info - Account & Payment:
get_payment_information,get_account_help,get_loyalty_program_info
- Order Management:
- Platform Agnostic: Strategy pattern for easy integration with any e-commerce platform
- Dynamic Mock Data: Intelligent test data system with pattern-based order behavior
- Dual Implementation Support: Gradio MCP server for web deployment, FastMCP for Claude Desktop STDIO integration
- Production Ready: CI/CD pipeline with automated deployment to Hugging Face Spaces
📋 Prerequisites
- Python 3.10 or higher
- pip package manager
- (Optional) Hugging Face account for deployment
🛠️ Installation
- Clone the repository:
git clone https://github.com/slavpilus/mcp.git
cd mcp
- Create and activate a virtual environment:
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
- Install dependencies:
pip install -r requirements.txt
🚀 Usage Options
Option 1: Gradio MCP Server (Recommended for Hugging Face Spaces)
Use the hosted Gradio MCP server on Hugging Face Spaces:
Gradio MCP Endpoint: https://huggingface.co/spaces/SlavPilus/mpc-for-commerce-platforms
Advantages:
- Native Gradio MCP server implementation with
mcp_server=True - No local setup required
- Always up-to-date with latest features
- Perfect for MCP-compatible clients and integrations
- Seamless Hugging Face Spaces deployment
Gradio MCP Server (local development)
python main.py
The Gradio MCP server starts on http://localhost:7860 with MCP SSE endpoint at http://localhost:7860/gradio_api/mcp/sse.
FastMCP Claude Desktop Integration (STDIO)
Step 1: Configure Claude Desktop
macOS: Edit ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: Edit %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"enneagora": {
"command": "python",
"args": ["/full/absolute/path/to/mcp/main_stdio.py"],
"env": {}
}
}
}
⚠️ Important:
- Use the full absolute path to
main_stdio.py - Ensure your Python environment has all dependencies installed
- Restart Claude Desktop after configuration changes
Step 2: Test Configuration
You can test the STDIO version manually:
python main_stdio.py
🔧 All Available Tools
Order Management Tools
- get_order_status - Get detailed order status and tracking information
- cancel_order - Cancel orders with validation checks
- process_return - Handle return requests with prepaid labels
- track_package - Track package delivery with real-time updates
Information & Support Tools
- get_support_info - General support information and guidance
- get_return_policy - Detailed return policies by product category
- get_shipping_info - Shipping rates, delivery times, and international options
- get_contact_information - Contact details by issue type and urgency
Product & Service Tools
- get_size_guide - Size charts for clothing, shoes, and accessories
- get_warranty_information - Warranty coverage and claims processing
- get_product_care_info - Care instructions and maintenance guidance
Account & Payment Tools
- get_payment_information - Payment methods, billing help, and troubleshooting
- get_account_help - Account troubleshooting and login assistance
- get_loyalty_program_info - Rewards program details and member benefits
🧪 Testing with Dynamic Mock Data
Enneagora features an intelligent mock data system where order behavior is determined by ID patterns:
Order Status Patterns
ORD-XXXX-D- Delivered orders (e.g., ORD-1001-D)ORD-XXXX-S- Shipped orders with tracking (e.g., ORD-1002-S)ORD-XXXX-T- In Transit with location updates (e.g., ORD-1003-T)ORD-XXXX-P- Processing orders (e.g., ORD-1004-P)ORD-XXXX-R- Ready for Pickup (e.g., ORD-1005-R)ORD-XXXX-C- Cancelled orders (e.g., ORD-1006-C)ORD-XXXX-F- Failed/Problem orders (e.g., ORD-1007-F)ORD-XXXX-E- Error/Not Found (e.g., ORD-1008-E)ORD-XXXX- Pending orders (no suffix, e.g., ORD-1009)
Example Queries
Once connected to Claude Desktop or an MCP client, you can use natural language:
Order Management:
- "Check the status of order ORD-1001-S"
- "Cancel order ORD-1004-P because I found a better price"
- "I want to return my order ORD-1002-D, it didn't fit properly"
Product Information:
- "What's your return policy for electronics?"
- "How much does shipping cost to Canada for a $45 order?"
- "What's the size guide for men's shirts?"
- "Is my laptop still under warranty? I bought it on 2023-06-15"
Account & Payment:
- "My credit card was declined, what should I do?"
- "I forgot my password, how can I reset it?"
- "How does your loyalty program work?"
Product Care:
- "How do I care for my silk dress?"
- "What's the best way to clean leather shoes?"
🏗️ Architecture
┌─────────────────────────────────────┐
│ MCP Clients │
│ (Claude Desktop, Web Clients) │
└──────────────┬──────────────────────┘
│ MCP Protocol Transport
┌──────────────▼──────────────────────┐
│ Dual MCP Implementation │
│ • main.py (Gradio MCP Server) │
│ • main_stdio.py (FastMCP STDIO) │
├─────────────────────────────────────┤
│ 14 MCP Tools: │
│ • Order Management (4 tools) │
│ • Information & Support (4 tools) │
│ • Product & Service (3 tools) │
│ • Account & Payment (3 tools) │
├─────────────────────────────────────┤
│ E-commerce Strategy Layer │
│ • Mock Strategy (Demo/Testing) │
│ • Shopify Strategy (Future) │
│ • Magento Strategy (Future) │
│ • WooCommerce Strategy (Future) │
└─────────────────────────────────────┘
🚢 Deployment
Hosted on Hugging Face Spaces
The server is deployed and accessible at:
- Web UI: https://huggingface.co/spaces/SlavPilus/mpc-for-commerce-platforms
- SSE Endpoint: https://huggingface.co/spaces/SlavPilus/mpc-for-commerce-platforms/sse
Manual Deployment
# Build Docker image
docker build -t enneagora .
# Run container
docker run -p 7860:7860 enneagora
Deploy Your Own Instance
- Fork this repository
- Set up GitHub secrets:
HF_TOKEN: Your Hugging Face tokenHF_USERNAME: Your Hugging Face usernameHF_SPACE_NAME: Name for your Space
- Push to main branch to trigger deployment
🧪 Development
Running Tests
# Install dev dependencies
pip install -r requirements-dev.txt
# Run tests with coverage
pytest --cov=mcp_server --cov=main
# Run linting and formatting
pre-commit run --all-files
Project Structure
mcp/
├── main.py # Gradio MCP server (mcp_server=True)
├── app.py # MCP tools for Gradio registration
├── main_stdio.py # FastMCP server (STDIO transport for Claude Desktop)
├── mcp_server/ # Core server implementation
│ ├── server.py # Main server logic
│ ├── mcp_tools.py # All 14 MCP tool definitions
│ └── strategies/ # E-commerce platform strategies
│ ├── base.py # Base strategy interface
│ └── mock_strategy.py # Mock data strategy
├── tests/ # Comprehensive test suite
│ ├── unit/ # Unit tests (96%+ coverage)
│ └── integration/ # Integration tests
├── static/ # Web UI assets
│ └── index.html # Server info and documentation page
├── requirements.txt # Python dependencies
├── requirements-dev.txt # Development dependencies
└── pyproject.toml # Project configuration
🔧 Configuration
Environment Variables
Currently uses mock data for demonstration. In production, configure:
ECOMMERCE_PLATFORM: Platform to use (e.g., "shopify", "magento")- Platform-specific credentials (API keys, endpoints, etc.)
Adding New E-commerce Platforms
- Create a new strategy in
mcp_server/strategies/:
from .base import EcommerceStrategy
class ShopifyStrategy(EcommerceStrategy):
async def get_order(self, order_id: str):
# Implement Shopify API integration
pass
- Register the strategy in your configuration
- Configure credentials and endpoints
📝 License
MIT License - see LICENSE file for details.
🤝 Contributing
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
🐛 Troubleshooting
Common Issues
-
Claude Desktop doesn't see the tools
- Verify the configuration file path and syntax
- Ensure you're using the full absolute path to
main_stdio.py - Check that Python environment has all dependencies
- Restart Claude Desktop after configuration changes
-
Server connection issues
- Ensure the server is running on the correct port
- Check firewall settings for local development
- Verify the SSE endpoint is accessible
-
Import errors or missing dependencies
- Activate your virtual environment
- Run
pip install -r requirements.txt - Ensure Python 3.10+ is installed
Testing Configuration
Test your local setup:
# Test STDIO version
python main_stdio.py
# Test SSE version
python main.py
# Then visit http://localhost:7860
📚 Resources
- Project Repository: https://github.com/slavpilus/mcp
- MCP Documentation: Model Context Protocol
- FastMCP Documentation: FastMCP GitHub
- Hugging Face Spaces: HF Spaces Documentation
🏆 Acknowledgments
Enneagora was built to demonstrate the power of Model Context Protocol for creating comprehensive AI-powered customer support systems as part of the Hugging Face MCP Hackathon. It showcases how MCP can bridge the gap between AI assistants and real-world e-commerce operations.
Key Features Demonstrated:
- Comprehensive tool ecosystem (14 interconnected tools)
- Dynamic mock data with intelligent behavior patterns
- Multi-transport support (SSE + STDIO)
- Production-ready deployment and CI/CD
- Type-safe implementation with 96%+ test coverage
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