The Spring AI Ecosystem in 2026: From Foundations to Agents
summary
Spring AI 2.0 ships concrete building blocks: ChatClient, advisors, memory, vector stores and RAG; JSON-schema outputs succeed ~99% with a looping advisor recovering most of the 1% failures. MCP (Model Context Protocol) gains annotations, session vs stateless transports, and enterprise security integrations. Recursive Advisors enable iterative tool calls and validation for MemGPT/Claude‑Code style agents. Tool search tool reduces token usage by ~50–70%. ACP and A2A provide IDE and agent-to-agent hooks; demos and open‑source code are available.
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chapters (9)
- 0:00Spring AI foundations
- 2:25Advisor pattern for state
- 5:11Context and RAG integration
- 7:36Guardrails and evaluation
- 13:41Autonomous tool calling
- 17:07Model context protocol
- 25:46Advanced context optimization
- 31:53Agent client protocol
- 42:14Roadmap and conclusion
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