https://blog.adriencaubel.fr/series/spring-ai/Recent content in Spring AI on Adrien CAUBELHugoenFri, 06 Nov 2026 00:00:00 +0000https://blog.adriencaubel.fr/posts/ai/spring-rag/Fri, 06 Nov 2026 00:00:00 +0000https://blog.adriencaubel.fr/posts/ai/spring-rag/Tip GitHub project : https://github.com/adrien1212/RAG-springai-poc.git In the previous article, we built a RAG with LangChain4j. In this post, we’ll build the same RAG using Spring AI. What is Spring AI ? Link to heading Like LangChain4J, Spring AI provides an unifies abractions over all major AI Model providers such as Anthropic, OpenAI, Microsoft, Amazon, Google, and Ollama, severals embedding models and vector stores. RAG Architecture Overview Link to heading To learn about RAG Architecture, please refer to the last article.https://blog.adriencaubel.fr/posts/ai/spring_mcp/Sat, 16 Aug 2025 00:00:00 +0000https://blog.adriencaubel.fr/posts/ai/spring_mcp/Tip GitHub project : https://github.com/adrien1212/spring-mcp-demo Introduction Link to heading Model Context Protocol (MCP) is a standard way for AI apps and agents to talk to external capabilities—databases, APIs, file systems, SaaS apps—without custom wiring each time. Instead of baking ad-hoc HTTP calls into your prompts, MCP gives you a consistent handshake to discover what capabilities are available, for exemple “Create a new Client” With MCP, you don’t manually hit REST endpoints.