Spring AI Agents Tutorial — Build a Tool-Calling AI Assistant (2026)

#springboot #angular #ai #tutorial

Canonical URL: Republished from munonye.com. Full code on GitHub.

🔥 Why this matters in 2026 — Agentic AI is the fastest-growing search topic in Java developer communities. Teams want LLMs that do things — query databases, call REST APIs, send emails — not just chat. This Spring AI agents tutorial shows the production pattern: ChatClient + @Tool on Spring Boot 3, the same stack as our Angular CRUD series.

Agentic AI is the defining backend trend of 2026. If you already ship Spring Boot REST APIs and Angular frontends, the next feature users expect is an AI assistant that acts on your data — look up orders, summarize tickets, recommend products — using tool calling, not prompt hacks.

This hands-on guide is part of the AI Developer Tutorials hub. You will build a tool-calling AI agent with Spring AI, step by step, in about 60 minutes.

Prerequisites: Spring AI first REST endpoint (M7-A), Java 17+, OpenAI API key, basic Spring Boot.

What is agentic AI?
Architecture overview
Step 1 — Define @Tool methods
Step 2 — Configure the agent ChatClient
Step 3 — REST API for the agent
Step 4 — Test multi-step prompts
Step 5 — Angular UI (optional)
Production checklist
FAQ

What is agentic AI? {#what-is-agentic-ai}

A Spring AI agent combines:

Component	Role
LLM	Plans steps and interprets user intent
@Tool methods	Your Java functions the model can invoke
ChatClient	Orchestrates the tool-calling loop

Unlike a basic chat endpoint (M7-A tutorial), an agent may execute multiple tool calls before answering — e.g. "What's the status of order 1042 and when will it ship?" → getOrder(1042) → getShippingEstimate(1042) → natural language summary.

💡 Tip: Start with 2–3 narrow tools. Agents fail when you expose twenty vague functions. Same lesson as microservices boundaries — see our Microservices hub.

Architecture overview {#architecture}

User prompt
    │
    ▼
POST /api/agent
    │
    ▼
ChatClient (Spring AI)
    ├──► LLM plans tool use
    ├──► @Tool getOrderStatus(orderId)
    ├──► @Tool listLowStockProducts()
    └──► Final answer to user

Stack alignment: This agent sits beside your existing FriendsAPI-style CRUD backend from the [complete CRUD guide](https://www.munonye.com/angu

Read the full tutorial with all code on munonye.com →

Full tutorial: Spring AI Agents Tutorial — Build a Tool-Calling AI Assistant (2026)

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