spring-ai

Configure Spring AI ChatClient and tool calling in Spring Boot applications.

1|Updated Mar 17, 2026

Search Tags:#rag #mcp #tool-calling #vector-store #spring-ai #prompt-template #chatclient

Ready to run

npx skills add https://github.com/iceflower/agent-skills --skill spring-ai-iceflower

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: spring-ai
Source: https://github.com/iceflower/agent-skills/tree/main/spring-ai
Command: npx skills add https://github.com/iceflower/agent-skills --skill spring-ai-iceflower

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Spring AI provides a structured set of conventions and patterns to streamline building AI-powered applications with Spring Boot, including ChatClient workflows, tool calling, prompt templates, vector store integration, RAG, MCP, and multi-model routing.

Core Features & Use Cases

Guides and patterns for integrating LLMs, ChatClient, tool calls, and Advisors within Spring.
Use cases span chat assistants, tooling orchestration, memory, and route-modeling across providers.

Quick Start

Initialize your Spring Boot application to adopt Spring AI conventions by configuring a ChatClient with the default system prompt and tools.

Frequently Asked Questions about spring-ai

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I configure ChatClient and tool calling in Spring Boot?▼

Yes, you can integrate vector stores and RAG in Spring AI by following structured conventions for vector store integration to build retrieval-augmented generation workflows.

What is the best way to structure prompt templates and multi-model routing in Spring AI?▼

Yes, MCP is supported in Spring AI through structured conventions that streamline building AI-powered applications with the Model Context Protocol within Spring Boot.

Do I need Spring Boot to use Spring AI patterns for AI applications?▼

Yes, you need Spring Boot because Spring AI provides a structured set of conventions specifically designed to streamline building AI-powered applications within the Spring Boot framework.

Can I use vector stores and RAG with Spring AI?▼

Yes, you can integrate vector stores and RAG in Spring AI by following structured conventions for vector store integration to build retrieval-augmented generation workflows.

What is the best way to structure prompt templates and multi-model routing in Spring AI?▼

The best way to structure prompt templates and multi-model routing in Spring AI is using its patterns to route requests across deployment scenarios and different providers.

Does Spring AI support MCP for building AI-powered applications?▼

Yes, MCP is supported in Spring AI through structured conventions that streamline building AI-powered applications with the Model Context Protocol within Spring Boot.