What technologies are used to build this API?

The API is built using Python 3.11+, Django 5.x, Django REST Framework, and SQLite for development. It also uses the python-dotenv package.

What is the Restaurant Ordering API?

It's a RESTful API built with Django REST Framework that simulates customer orders from a dummy restaurant menu. It allows for real-time order status tracking and easy integration with MCP systems.

How can I use the API to track recent orders?

You can use the `/api/orders/recent/?hours=X` endpoint, replacing `X` with the number of hours. For example, `/api/orders/recent/?hours=2` will retrieve orders from the last 2 hours.

Is the API suitable for production environments?

The current version uses SQLite which is more suitable for development. For production, consider switching to a more robust database like PostgreSQL and implementing proper authentication and authorization.

What does MCP stand for in this context?

MCP stands for Model-Context-Protocol. The API is designed following this pattern, making it ideal for integration with AI/automation pipelines where structured data, temporal context, and clean APIs matter.

Restaurant Ordering API: Simulate & Track Orders

This Python-based server, built with Django and Django REST Framework, provides a RESTful API for simulating restaurant orders. It's designed to integrate seamlessly with Model-Context-Protocol (MCP) architectures, making it ideal for testing and development within larger AI and automation pipelines. The server allows users to create, track, update, and delete orders, as well as retrieve recent order history. It serves as a dummy restaurant ordering system where customers can order, track status, and view their order history, making it perfect for anyone needing a plug-and-play solution for MCP integrations.

Key Features

010 GitHub stars

02Ability to view recent orders based on time frame

03Fully RESTful API design

04Easy integration with MCP systems

05Includes example cURL commands for quick testing

06Real-time order status tracking (success/failed)

Use Cases

01Building AI-powered food court assistants

02Simulating customer order workflows

03Testing and development of MCP integrations

Restaurant Ordering API

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Discord Integration

Restaurant Ordering API

Key Features

Use Cases

Neon

Firecrawl

Figma Context

Diagram Maker & Visualizer

GH Issues Auto-Fixer

Discord Integration

Key Features

Use Cases