Utilizes jQuery for frontend interactions in the real-time chat interface.
Built on Laravel framework to power the backend of this e-commerce order management system with AI chat functionality.
Supports MySQL as an alternative database option for storing product and order information.
Integrates with OpenAI's GPT-3.5-turbo model to process natural language queries in Traditional Chinese, enabling intelligent responses about orders and products based on database information.
Uses SQLite as the default database for storing and querying product and order information.
Implements Tailwind CSS for the responsive design of the user interface.
MCP Demo Project
A Laravel-based Model Context Protocol (MCP) demonstration project featuring an e-commerce order management system with AI-powered chat functionality using OpenAI.
Features
Order Management: Display and manage customer orders with pagination
Product Catalog: Browse supermarket products (sodas, chips, ice cream, etc.)
AI Chat Interface: Query order and product data using natural language in Traditional Chinese
Database Integration: SQLite database with seeded sample data
Modern UI: Responsive design using Tailwind CSS
Project Structure
Models
Product: Represents supermarket items with name, price, description, stock, and category
Order: Customer orders with transaction ID, customer name, amount, status, and product relationships
Database Schema
Products Table
id
- Primary keyname
- Product name (Traditional Chinese)description
- Product descriptionprice
- Product price (HKD)stock_quantity
- Available stockcategory
- Product category (飲料, 零食, 雪糕)created_at
,updated_at
- Timestamps
Orders Table
id
- Primary keytransaction_id
- Unique transaction identifier (TXN######)name
- Customer name (Traditional Chinese)amount
- Order total amountstatus
- Order status (pending, processing, completed, cancelled, refunded)product_id
- Foreign key to products tablequantity
- Quantity orderedcreated_at
,updated_at
- Timestamps
Sample Data
10 Products: Supermarket items including:
可口可樂 (Coca-Cola)
樂事薯片 (Lay's Chips)
哈根達斯雪糕 (Häagen-Dazs Ice Cream)
百事可樂 (Pepsi)
And more...
500 Orders: Randomly generated orders with:
Unique transaction IDs
Chinese customer names
Random products and quantities
Various order statuses
Realistic timestamps
AI Chat Functionality
The AI chat interface uses OpenAI's GPT-3.5-turbo model to answer queries about orders and products. The system:
Processes natural language queries in Traditional Chinese
Searches relevant data based on keywords and patterns
Provides context to the AI model with retrieved data
Returns intelligent responses about orders and products
Example Queries
"顯示所有已完成的訂單" (Show all completed orders)
"TXN000001 的訂單詳情" (Details for order TXN000001)
"陳大明的所有訂單" (All orders for customer 陳大明)
"有什麼飲料產品?" (What beverage products are available?)
Installation & Setup
Prerequisites
PHP 8.1+
Composer
Node.js & npm (optional, for asset compilation)
Installation Steps
Clone the repository
git clone <repository-url> cd mcp_demoInstall dependencies
composer installEnvironment setup
cp .env.example .env php artisan key:generateConfigure OpenAI API Add your OpenAI API key to
.env
:OPENAI_API_KEY=your_openai_api_key_hereDatabase setup The project is configured to use SQLite by default:
php artisan migrate php artisan db:seedStart the server
php artisan serveAccess the application Open your browser and navigate to
http://127.0.0.1:8000
Configuration
Database Configuration
SQLite (Default)
MySQL (Alternative)
For MySQL, create the database first:
OpenAI Configuration
Usage
Main Dashboard
View paginated list of orders with details
Browse product catalog
Use AI chat to query data
AI Chat Interface
The chat interface supports various query types:
Order lookup by transaction ID
Customer order history
Product searches
Status-based filtering
General inquiries about the data
API Endpoints
GET /
- Main dashboardPOST /chat
- AI chat endpoint
Technical Implementation
MCP Integration
The project demonstrates MCP concepts by:
Data Retrieval: Structured database queries based on AI prompts
Context Building: Formatting retrieved data for AI consumption
Response Generation: Using OpenAI to generate intelligent responses
User Interface: Real-time chat interface for natural language queries
Technologies Used
Backend: Laravel 12, PHP 8.1+
Database: SQLite/MySQL
AI: OpenAI GPT-3.5-turbo
Frontend: Blade templates, Tailwind CSS, jQuery
HTTP Client: OpenAI PHP Client
Development
Adding New Features
Create new models/controllers as needed
Update database migrations and seeders
Extend the chat functionality in
ChatController
Add new UI components to the dashboard
Testing
Code Style
Troubleshooting
Database Issues
Ensure SQLite is enabled in PHP
For MySQL, check connection credentials
Run
php artisan config:clear
after configuration changes
OpenAI Issues
Verify API key is correct
Check API quota and usage limits
Ensure internet connectivity
Performance
Consider adding database indexes for large datasets
Implement caching for frequently accessed data
Use Laravel queues for heavy AI operations
License
This project is open-sourced software licensed under the MIT license.
Contributing
Fork the repository
Create a feature branch
Make your changes
Submit a pull request
Support
For issues or questions, please create an issue in the repository or contact the development team.
This server cannot be installed
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
A Laravel-based Model Context Protocol demonstration that enables users to manage orders and query e-commerce data in Traditional Chinese through an AI-powered chat interface.
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