Building a Simple AI Agent with Micronaut, MCP, and LangChain4j
AI agents can feel complicated when you first explore them. Many guides jump into deep theory or large architectures too quickly. However, it does not have to be that way. This post introduces a straightforward way to build a simple AI agent using Micronaut, MCP, and LangChain4j , while keeping everything practical and easy to follow. If you would like a detailed, step-by-step guide, you can read the full article here: 👉 https://dev.to/jobinesh/building-a-simple-ai-agent-with-micronaut-mcp-and-langchain4j-21k6 The Basic Idea At a high level, an AI agent consists of three main parts: A model that understands and generates responses A set of tools that perform actions Some code that connects everything together That is all you need to get started. Why This Stack Works Well This combination of technologies keeps things simple: Micronaut is lightweight and fast. LangChain4j makes it easy to integrate large language models in Java. MCP allows the agent to interact with tools in a struct...