How are tool parameters optimized for LLMs?

The skill provides patterns for detailed @ToolParam descriptions and examples, which help LLMs understand exactly what data to pass and in what format.

Does this skill support local LLM models?

Yes, it includes specific configurations for running local models like Llama 3.1 via Ollama alongside cloud-based models like Grok.

Is this skill suitable for production AI agents?

Absolutely. By enforcing use case validation and domain modeling, it prevents common issues where LLMs might trigger incorrect or unvalidated business actions.

What database technologies are compatible with this pattern?

The pattern is database-agnostic; while the example uses ClickHouse via JDBC, the Clean Architecture approach allows you to swap in any persistence layer.

What is the core benefit of using DDD with Spring AI MCP?

Using DDD ensures that AI tool definitions remain in the infrastructure layer while business logic is protected in the domain and application layers, making the system easier to test and maintain.

Spring AI MCP Architecture

Name: Spring AI MCP Architecture
Author: reynierre

byreynierre

0•

API 开发

Implements Model Context Protocol tools using Spring AI and Domain-Driven Design for robust, clean retail analytics integrations.

This skill provides a comprehensive blueprint for developing Model Context Protocol (MCP) tools within the Spring AI ecosystem. By leveraging Clean Architecture and Domain-Driven Design (DDD), it ensures a strict separation between tool definitions in the infrastructure layer and core business logic in the application layer. It is specifically designed for developers building conversational retail analytics systems, providing standardized patterns for tool annotations, parameter descriptions, and multi-model configurations (Grok/Ollama) to ensure LLMs interact reliably with enterprise data sources.

主要功能

01Clean Architecture implementation for MCP tool delegation

02Standardized Spring AI tool and parameter annotations

03Best practices for LLM-optimized tool descriptions

04Domain-Driven Design patterns for AI tool development

05Multi-model support for Grok and local Ollama deployments

060 GitHub stars

使用场景

01Standardizing MCP tool definitions across Spring Boot microservices

02Implementing enterprise AI agents with decoupled business logic

03Building conversational retail analytics interfaces for store performance

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add reynierre/geo-retail-analytics-mcp spring-ai-mcp

For use in Claude.ai and ChatGPT

Download Skill