Quarkus MCP Agentic
What is this application?
This application demonstrates how to build AI-powered agents using Quarkus (a Java framework) and multiple MCP servers. It connects to various services like Brave Search, Google Maps, Slack, and OpenAI to perform complex tasks through natural language prompts.How does it work?
The application uses LangChain4j to orchestrate multiple MCP services. You interact with it through natural language prompts, and it intelligently decides which services to use to complete your requests.Use Cases
Ideal for team coordination tasks like finding restaurants that meet dietary needs, scheduling meetings, sending invitations, and creating calendar events - all through simple chat-like interactions.Key Features
Multi-service IntegrationSeamlessly combines multiple MCP services (Brave Search, Google Maps, Slack, OpenAI) to complete complex tasks
Natural Language InterfaceUnderstands and executes tasks through conversational prompts in plain English
Contextual MemoryRemembers team preferences and previous interactions to provide personalized responses
Automated WorkflowsPerforms multi-step workflows automatically (search → select → notify → schedule)
Pros and Cons
Advantages
Handles complex multi-service workflows with a single prompt
Remembers context between interactions
Open architecture allows adding new services easily
Built-in development UI for testing and debugging
Limitations
Requires API keys for external services
Needs Node.js and container runtime for full functionality
Current version focuses on specific use cases (team coordination)
Getting Started
Install Prerequisites
Install Node.js/npm and Docker/Podman for container support
Set Up API Keys
Create a .env file with your API keys for Brave Search, Google Maps, Slack, and OpenAI
Run in Development Mode
Start the application with live reload enabled
Access the Interface
Open http://localhost:8080 in your browser and use the chat interface
Example Use Cases
Team Lunch CoordinationFind a restaurant that meets team dietary needs, invite members via Slack, and create calendar events
Information RecallAsk about previous decisions and reasoning
Frequently Asked Questions
Do I need all the API keys to try the application?
Can I change the Slack channel it posts to?
Where are generated files (like ICS) stored?
How do I see what services are being used?
Additional Resources
Quarkus Framework
The Java framework used to build this application
Model Context Protocol
Official MCP documentation
LangChain4j Quarkus Extension
Integration between Quarkus and LangChain4j
GitHub Repository
Source code for MCP servers
精选MCP服务推荐

Figma Context MCP
Framelink Figma MCP Server是一个为AI编程工具(如Cursor)提供Figma设计数据访问的服务器,通过简化Figma API响应,帮助AI更准确地实现设计到代码的一键转换。
TypeScript
6.8K
4.5分

Duckduckgo MCP Server
已认证
DuckDuckGo搜索MCP服务器,为Claude等LLM提供网页搜索和内容抓取服务
Python
976
4.3分

Firecrawl MCP Server
Firecrawl MCP Server是一个集成Firecrawl网页抓取能力的模型上下文协议服务器,提供丰富的网页抓取、搜索和内容提取功能。
TypeScript
4.1K
5分

Edgeone Pages MCP Server
EdgeOne Pages MCP是一个通过MCP协议快速部署HTML内容到EdgeOne Pages并获取公开URL的服务
TypeScript
325
4.8分

Context7
Context7 MCP是一个为AI编程助手提供实时、版本特定文档和代码示例的服务,通过Model Context Protocol直接集成到提示中,解决LLM使用过时信息的问题。
TypeScript
5.4K
4.7分

Exa Web Search
已认证
Exa MCP Server是一个为AI助手(如Claude)提供网络搜索功能的服务器,通过Exa AI搜索API实现实时、安全的网络信息获取。
TypeScript
1.9K
5分

Baidu Map
已认证
百度地图MCP Server是国内首个兼容MCP协议的地图服务,提供地理编码、路线规划等10个标准化API接口,支持Python和Typescript快速接入,赋能智能体实现地图相关功能。
Python
823
4.5分

Minimax MCP Server
MiniMax Model Context Protocol (MCP) 是一个官方服务器,支持与强大的文本转语音、视频/图像生成API交互,适用于多种客户端工具如Claude Desktop、Cursor等。
Python
904
4.8分
智启未来,您的人工智能解决方案智库
简体中文