Which core technologies are used in this backend?

The backend is built with FastAPI, uses PostgreSQL for database management, and is containerized using Docker and Docker Compose. It also features MCP for LLM integration.

What is the Appointment API Backend?

It's a foundational FastAPI application designed for managing appointments. It uses PostgreSQL for data persistence, Docker for containerization, and integrates with LLMs via the Model Context Protocol (MCP).

How does this backend support integration with Large Language Models (LLMs)?

It includes Model Context Protocol (MCP) integration, exposing its API endpoints via `mcp-openapi-proxy` so LLMs like Claude can seamlessly use them as external tools.

What kind of appointment management features does it offer?

It provides full CRUD (Create, Read, Update, Delete) operations for appointments, allowing users to create, list, modify, and remove appointment records through its API endpoints.

Appointment API Backend

Name: Appointment API Backend
Author: Samuelr2112

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Establishes a foundational FastAPI application for managing appointments, integrating PostgreSQL, and containerizing with Docker for Model Context Protocol exposure.

This project serves as a robust initial checkpoint for building an API-driven application, demonstrating a complete setup from environment configuration to deployment readiness. It features a simple yet functional FastAPI backend capable of handling appointment-related operations (create, list, update, delete). The data is persistently stored in a PostgreSQL database, all neatly packaged and managed with Docker Compose. Crucially, it's configured for seamless integration with the Model Context Protocol (MCP), allowing its API endpoints to be utilized as tools through large language models like Claude, showcasing a practical application of modern API development and LLM tool integration.

Key Features

011 GitHub stars

02Python virtual environment for dependency management

03FastAPI backend with CRUD endpoints for appointments

04PostgreSQL database integration for data persistence

05Docker and Docker Compose for containerized deployment

06MCP integration for exposing API endpoints to LLMs

Use Cases

01Setting up a basic API backend for scheduling or booking systems

02Learning and demonstrating FastAPI and PostgreSQL integration with Docker

03Exposing custom APIs as tools for large language models via MCP