MCP -build-using-Spring-AI-and-Java

The MCP Server built using Spring AI and Java is designed to facilitate the implementation of the Model Context Protocol, enabling seamless interaction between various AI models and applications. Developers can utilize this server to efficiently manage model contexts, enhance data flow, and optimize AI operations, making it an essential tool for applications requiring robust AI integration.

Once connected to the MCP Server, you can interact with it by sending HTTP requests to predefined endpoints. The server allows you to perform actions such as creating, retrieving, updating, and deleting model contexts. You can use tools like Postman or cURL to send JSON-formatted payloads, which are ideal for executing commands such as /create-context or /get-context. Make sure to structure your queries according to the API documentation available in the GitHub repository.

To install the MCP Server, ensure you have the following prerequisites:

• Java Development Kit (JDK) 11 or higher
• Apache Maven (for building the project)

Option A: If you prefer a quick start, you can clone the repository and build it directly:

git clone https://github.com/HarshilChampaneri/MCP-Server-build-using-Spring-AI-and-Java.git
cd MCP-Server-build-using-Spring-AI-and-Java
mvn clean install

Option B: For a global installation, you can build the project into a JAR file and run it:

mvn package
java -jar target/mcp-server.jar

For optimal performance, consider configuring your server's environment variables, such as SPRING_DATASOURCE_URL for database connections and SPRING_PROFILES_ACTIVE to specify the active profile. A common gotcha is ensuring that your database is properly set up and accessible by the server, as misconfigured database connections can lead to runtime errors.