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Quickstart - Spring Step 1: Start a new Spring Boot project Use start spring io to create a “web” project In the “Dependencies” dialog search for and add the “web” dependency as shown in the screenshot Hit the “Generate” button, download the zip, and unpack it into a folder on your computer
Spring | Home Most [of our] services today are all based on Spring Boot I think the most important thing is that [Spring] has just been very well maintained over the years that is important for us for the long term because we don’t want to be switching to a new framework every two years
Developing Your First Spring Boot Application The final part of our application is the main method This is a standard method that follows the Java convention for an application entry point Our main method delegates to Spring Boot’s SpringApplication class by calling run SpringApplication bootstraps our application, starting Spring, which, in turn, starts the auto-configured Tomcat web server We need to pass MyApplication class as
Java Spring MCP :: Spring AI Reference Java SDK and Spring Framework integration for the Model Context Protocol, enabling standardized interaction with AI models and tools through both synchronous and asynchronous communication
MCP Client Boot Starter :: Spring AI Reference Request Configuration - Set custom request timeouts Custom Sampling Handlers - standardized way for servers to request LLM sampling (completions or generations) from LLMs via clients This flow allows clients to maintain control over model access, selection, and permissions while enabling servers to leverage AI capabilities — with no server API keys necessary
Model Context Protocol (MCP) :: Spring AI Reference Client Server Layer: The McpClient handles client-side operations while the McpServer manages server-side protocol operations Both utilize McpSession for communication management Session Layer (McpSession): Manages communication patterns and state through the DefaultMcpSession implementation Transport Layer (McpTransport): Handles JSON-RPC message serialization and deserialization with
Chat Memory :: Spring AI Reference The ChatMemory abstraction is designed to manage the chat memory It allows you to store and retrieve messages that are relevant to the current conversation context However, it is not the best fit for storing the chat history If you need to maintain a complete record of all the messages exchanged, you should consider using a different approach, such as relying on Spring Data for efficient