Quarkus MCP Agentic
Q

Quarkus MCP Agentic

This project uses the Quarkus framework and the Model Context Protocol (MCP) to implement an intelligent agent application based on multiple MCP servers. It combines LangChain4j to provide functions such as AI dialogue, restaurant recommendation, and Slack notification, and supports deployment in development and production environments.
2 points
8.2K

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 Integration
Seamlessly combines multiple MCP services (Brave Search, Google Maps, Slack, OpenAI) to complete complex tasks
Natural Language Interface
Understands and executes tasks through conversational prompts in plain English
Contextual Memory
Remembers team preferences and previous interactions to provide personalized responses
Automated Workflows
Performs multi-step workflows automatically (search → select → notify → schedule)
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 Coordination
Find a restaurant that meets team dietary needs, invite members via Slack, and create calendar events
Information Recall
Ask 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

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

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