MCP Server Appointment Management

🚀 MCP Server Reservation Management Project

This project is a Java-based MCP (Model-Context-Protocol) server designed to manage reservation data from a database. It offers a modular framework, exposes internal tools for data analysis and operations, and comes with built-in support for AI-driven features.

🚀 Quick Start

This is a Java-based MCP server for managing reservation data from a database. It provides a modular framework, exposes internal tools for data analysis and operations, and has built-in support for AI-driven features.

✨ Features

• User verification and authentication
• Reservation scheduling and management
• Integration with PostgreSQL or MySQL databases (support for other databases available)

📦 Installation

Prerequisites

• Java 17 or higher
• Maven 3.6+
• PostgreSQL or MySQL - Other databases can be used*
• Spring Boot
• Spring AI 1.0.0-M7

Database Configuration

Before running the application, configure your database connection. The current server supports PostgreSQL and MySQL. To connect to the database, update the application.properties file in the src/main/resources folder to provide your database configuration:

spring.datasource.url=jdbc:postgresql://localhost:5432/demodb
spring.datasource.username=admin
spring.datasource.password=adminpw

spring.jpa.properties.hibernate.dialect=org.hibernate.dialect.PostgreSQLDialect
spring.jpa.hibernate.ddl-auto=update
spring.jpa.show-sql=true

🔧 Technical Details

Token-based Authentication and Authorization

In this application, tokens are used for user authentication and authorization. Once a user's identity is verified, the system generates a temporary token. This token serves as the key for performing operations such as creating, updating, or canceling reservations. Every MCP request must include this token to ensure the operation is authorized.

You can change or extend the authentication method to meet your needs. For example, you can implement a user login function.

Token Workflow Example:

1. A user requests a token by providing their credentials.
2. After successful verification, the system generates a temporary token.
3. Use the token for subsequent reservation management operations.
4. The token expires after a preset period or can be manually revoked.

Reservation Management

This system supports the following reservation management functions:

1. Create a Reservation The system allows users to create new reservations. Once a user is authenticated and authorized, they can submit a new reservation request and provide the necessary details (such as time, date, and participants).

2. Update a Reservation Users with a valid token can update the details of an existing reservation. This includes changing the time, participants, or reservation status.

3. Cancel a Reservation Users can cancel a reservation using the system. Once canceled, the reservation will be deleted from the database, and relevant notifications will be sent.

AI-driven Features

The application uses the MCP protocol, ensuring the security of the internal database while still allowing AI to perform critical data operations. This protocol layer provides a secure way for the AI system to access and operate on data, protecting sensitive information and ensuring that only authorized operations are performed.

Potential Application Scenarios

Combining MCP with AI tools opens up exciting possibilities for various AI-driven applications:

Chatbot Integration

With the AI reservation tools exposed through MCP, chatbots can assist users in making, updating, and canceling reservations. These chatbots can understand the user's context and provide intelligent suggestions based on their availability and preferences.

Intelligent Reservation Assistant

An AI-driven reservation assistant can automatically schedule, reschedule, or cancel reservations for users based on their calendars and priorities, without direct human intervention.

Automated Conflict Resolution

AI can proactively resolve reservation time conflicts. If two users try to book the same time slot, the AI can automatically suggest an alternative, minimizing human intervention.

🤝 Contribution Guidelines

We welcome your contributions! If you wish to contribute to this project, please follow these steps:

1. Fork this repository.
2. Create a new branch for your feature development: git checkout -b feature/your-feature-name
3. Commit your changes: git commit -m 'Describe the changes you've made'
4. Push to your forked repository: git push origin feature/your-feature-name
5. Create a pull request to merge your branch into the main branch.

Please ensure you read and follow the project's contribution guidelines and code standards before submitting a pull request. Thank you for your support!