Agentic TiDB CRUD Example

This is a Spring Boot project that demonstrates CRUD operations using TiDB (a MySQL-compatible distributed database). The project integrates with OpenAI's GPT-4 model for AI-based functionalities and leverages the MCP @Tool framework to enable agentic capabilities.

Features

• Agentic capabilities with MCP @Tool
• CRUD operations with TiDB
• Spring AI integration using OpenAI GPT-4 via Spring AI
• Spring Boot-based architecture
• Logging and debugging enabled for development
• Memory persistence using JDBC-based chat history

Prerequisites

• Java 17 or higher
• Maven 3.6 or higher
• TiDB Cloud account
• OpenAI API key

User Interface Preview

The app comes with a built-in chat interface for interacting with your AI agent and CRUD tools.
File: src/main/resources/templates/chat.html

Chat UI Screenshot

Setup Instructions

1. Clone the Repository

   git clone <repository-url>
   cd <repository-folder>

2. Configure the Application Update the src/main/resources/application.properties file with your TiDB and OpenAI credentials.

     spring.datasource.url=jdbc:mysql://<tidb-endpoint>/<database>?sslMode=VERIFY_IDENTITY
     spring.datasource.username=<username>
     spring.datasource.password=<password>
     spring.ai.openai.api-key=<your-openai-key>
   

3. Build the Project

   mvn clean install

4. Run the Application

   mvn spring-boot:run

5. Access the Application The application will be available at http://localhost:8080.

Database Schema

The schema is initialized using the schema-ai-memory.sql file. Ensure the spring.sql.init.mode property is set to always in application.properties.

spring.sql.init.mode=always

Testing

Run the tests using:

mvn test

Logging

Logging is configured in application.properties for debugging purposes. Adjust the logging levels as needed.

logging.level.org.springframework.web=DEBUG
logging.level.org.springframework.ai=DEBUG

Agentic Capabilities

This project uses the MCP @Tool framework to enable agentic functionalities. The @Tool annotations allow seamless integration with OpenAI's GPT-4 model, enabling advanced AI-driven operations.

Example:

@Tool(name = "createUser", description = "Creates a new user in the database")
public User createUser(String name, String email) {
    return repository.save(new User(name, email));
}

This allows GPT-4 to call real application methods to perform CRUD operations — effectively turning your backend into an agentic API.