Tag Archives: RESTful

AI Interoperability with MCP (and a Spring MCP Server example)

Model Context Protocol (MCP) is a structured, interoperable standard that enables AI agents to query, invoke, and respond to external APIs or services. Think of MCP as a universal translator that allows Large Language Models (LLMs) like Claude to seamlessly connect with databases, APIs, file systems, and other services through a standardized interface.

At its core, MCP solves a critical AI development problem: the fragmented integrations landscape. Before MCP, each AI application required custom connectors and bespoke integrations for every external service it needed to access. MCP standardizes this process through a client-server architecture where AI applications act as MCP clients and external services expose themselves through MCP servers.

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Integrating Spring AI Framework in Your Java Application

This blog post will integrate the Spring AI framework into a Java application. We’ll use a simple project that includes a ChatService and a ChatController to demonstrate using the Spring AI framework to generate text & image responses and horoscopes based on user input.

Update 12/28/2025 – Updated from M1 release to Spring AI 1.1.0 GA

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