π½οΈ MCP Restaurant Ordering API Server
LocalAbout π½οΈ MCP Restaurant Ordering API Server
MCP Restaurant Ordering API Server is a sample restaurant-ordering API built with Django REST Framework, intended for testing API and MCP integrations. It supports order creation, lookup, updates, and status tracking for a dummy menu.
Key features
- 01Create and manage orders
- 02Retrieve order details and history
- 03Filter recent orders by time range
- 04Track success or failure status
Use cases
- 01Test restaurant-order API integrations
- 02Review orders from a chosen time window
- 03Simulate successful and failed orders
MCP support
The project describes its RESTful API as an example following the MCP pattern, but the README does not specify tools exposed to MCP clients or a connection method.
Configuration
Local server config is the same for every client. Copy it into your clientβs MCP config file.
We havenβt collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEπ½οΈ MCP Restaurant Ordering API Server
Welcome to the MCP-compatible Restaurant API built with Django + Django REST Framework.
Simulate customer orders from a dummy restaurant menu and track their status in real-time . Ideal for integration with any MCP server.
π§ Why MCP Server?
We call this an MCP server because it follows the Model-Context-Protocol pattern:
- Model β The
Ordermodel defines the data structure (items, status, time). - Context β Recent queries like
/recent/?hours=2give contextual insights (e.g., last 2 hours). - Protocol β RESTful APIs define a structured communication protocol.
Think of it like a food court AI assistant:
π Model = What's on the menu
β° Context = What's trending now
π‘ Protocol = How it communicates with you (API)
This makes it ideal for plugging into larger AI/automation pipelines where structured data, temporal context, and clean APIs matter.
π Project Directory
βββ mcp_server/
β βββ requirements.txt
β βββ db.sqlite3
β βββ README.md
β βββ .env
β βββ manage.py
β βββ orders/
β β βββ models.py
β β βββ serializers.py
β β βββ apps.py
β β βββ admin.py
β β βββ tests.py
β β βββ urls.py
β β βββ views.py
β βββ mcp_server/
β β βββ asgi.py
β β βββ settings.py
β β βββ urls.py
β β βββ wsgi.py
π Quickstart
# 1. Clone the repo
git clone https://github.com/sachnaror/restaurant-mcp-server.git
cd restaurant-mcp-server
# 2. Setup environment
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
# 3. Add secrets to `.env`
echo "SECRET_KEY=your_django_secret_key" > .env
echo "DEBUG=True" >> .env
# 4. Run DB & server
python manage.py migrate
python manage.py runserver
π§ͺ Example Usage (cURL)
# Create a new order
curl -X POST http://localhost:8000/api/orders/ \
-H "Content-Type: application/json" \
-d '{"item_name": "Biryani", "status": "success"}'
# Get recent orders in last 2 hours
curl http://localhost:8000/api/orders/recent/?hours=2
π API Endpoints
Base URL: http://localhost:8000/api/
| Method | Endpoint | Description | Sample Payload |
|---|---|---|---|
POST | /api/orders/ | π Place a new order | { "item_name": "Pizza", "status": "success" } |
GET | /api/orders/ | π List all orders | β |
GET | /api/orders/{id}/ | π Get single order by ID | β |
PUT | /api/orders/{id}/ | βοΈ Update an order | { "item_name": "Burger", "status": "failed" } |
DELETE | /api/orders/{id}/ | ποΈ Delete an order | β |
GET | /api/orders/recent/?hours=2 | β±οΈ Get orders from last 2 hours | β |
π§ Tech Stack
- π Python 3.11+
- π§± Django 5.x
- π Django REST Framework
- π SQLite (Dev DB)
- π¦ python-dotenv
π Roadmap (Ideas)
- π Token-based user authentication (optional)
- π Dashboard for order analytics
- π₯ Webhook or async order processing simulation
- π§ OpenAI GPT integration for dynamic menu or chat
πΈ Screenshots
π© Contact
| Name | Details |
|---|---|
| π¨βπ» Developer | Sachin Arora |
| π§ Email | [email protected] |
| π Location | Noida, India |
| π GitHub | github.com/sachnaror |
| π Website | https://about.me/sachin-arora |
| π± Phone | +91 9560330483 |
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.