What programming environment is required?
The workshop assumes Java, Maven, and a Quarkus development environment. The application runs with `./mvnw quarkus:dev` which uses Maven wrapper.
@quarkusio
基本信息
Quarkus LangChain4J Workshop that demonstrates both single AI service capabilities and Agentic AI orchestration
工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
quarkus-langchain4j-workshop is a hands-on workshop to learn how to build AI-infused applications using Quarkus and LangChain4j. It is divided into several steps, with final code available in step-XX directories.
Follow the instructions on the workshop website or serve them locally using the docs/README file. To run the final state of a step, navigate to its directory and run ./mvnw quarkus:dev; the application runs on localhost:8080.
The workshop assumes Java, Maven, and a Quarkus development environment. The application runs with `./mvnw quarkus:dev` which uses Maven wrapper.
Each step has a dedicated directory named `step-XX` containing the final state of that step.
Instructions are available on the workshop website or locally by following the docs/README file.
This is a very basic implementation of an Mcp-Reasoning-Server for Cursor AI .
This project demonstrates a decoupled real-time agent architecture that connects LangGraph agents to remote tools served by custom MCP (Modular Command Protocol) servers. The architecture enables a flexible and scalable multi-agent system where each tool can be hosted independent
MCP server that gives Claude persistent project memory — roadmap, session history, and codebase context. Type continue and Claude picks up exactly where you left off
# 🐢🚀 Node.js Sandbox MCP ServerThis repository hosts a Node.js server that implements the Model Context Protocol (MCP) for running JavaScript in isolated Docker containers. It allows for on-the-fly npm dependency installation, making it easy to execute code safely and efficient
Neuronto Agentic Resource Discovery (ARD) Index. Federated search across every public ARD registry, plus a verified tool index read from each MCP server's own tools/list, hybrid lexical and semantic retrieval, and ARD-Bench.
评论