Quarkus LangChain4J
Quarkus LangChain4J Workshop
What is Quarkus LangChain4J?
Quarkus LangChain4J is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to quarkus langchain4j workshop
Quarkus LangChain4J Workshop
This server falls under the Developer Tools category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- Quarkus LangChain4J Workshop
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx quarkus-workshop-langchain4jConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Quarkus LangChain4J
The Quarkus LangChain4J Workshop is a hands-on, structured learning project that guides Java developers through building AI-infused applications using the Quarkus framework and its LangChain4j integration. Organized as a series of progressive step directories, each containing the complete code state for that phase, the workshop covers connecting Quarkus services to LLMs, implementing AI services with annotations, streaming responses, memory-aware chatbots, and MCP tool integration. Developers use it to quickly learn how to embed LLM capabilities into production-grade Quarkus microservices using familiar Java patterns.
Prerequisites
- Java 17 or later installed (Java 21 LTS recommended for Quarkus 3.x)
- Maven 3.9+ or use the included ./mvnw wrapper
- Git to clone the repository
- An LLM API key (OpenAI or a compatible provider such as Ollama for local models)
- An MCP-compatible client or IDE if using the MCP integration steps
Clone the workshop repository
Clone the quarkus-workshop-langchain4j repository from GitHub. The workshop is organized into numbered step directories (step-00 through step-XX).
git clone https://github.com/quarkusio/quarkus-workshop-langchain4j.git
cd quarkus-workshop-langchain4jRead the workshop instructions
Open the workshop website or browse the docs/ directory for step-by-step instructions. Each step builds on the previous one, adding new AI capabilities to the Quarkus application.
ls docs/
# Or visit: https://quarkusio.github.io/quarkus-workshop-langchain4jConfigure your LLM API key
Each step directory contains an application.properties or .env file where you set your LLM provider API key. For OpenAI-compatible providers, set the quarkus.langchain4j.openai.api-key property.
# In step-01/src/main/resources/application.properties:
quarkus.langchain4j.openai.api-key=sk-your-openai-api-key-here
quarkus.langchain4j.openai.chat-model.model-name=gpt-4o-miniStart a workshop step in dev mode
Navigate to a step directory and start the Quarkus development server. Hot-reload is enabled so code changes apply immediately without restarting.
cd step-01
./mvnw quarkus:devAccess the running application
Once the dev server starts, open http://localhost:8080 in your browser to interact with the AI-infused Quarkus application for that workshop step. The Quarkus Dev UI is available at http://localhost:8080/q/dev.
Quarkus LangChain4J Examples
Client configuration
Example application.properties for a Quarkus LangChain4J app using OpenAI as the LLM provider.
{
"note": "Quarkus uses application.properties, not JSON MCP config",
"file": "src/main/resources/application.properties",
"properties": {
"quarkus.langchain4j.openai.api-key": "sk-your-openai-api-key",
"quarkus.langchain4j.openai.chat-model.model-name": "gpt-4o-mini",
"quarkus.langchain4j.openai.timeout": "60s",
"quarkus.http.port": "8080"
}
}Prompts to try
What you will build and test through the workshop steps.
- Open http://localhost:8080 and chat with the AI assistant built in the current step
- Ask the Quarkus chatbot: "What are the workshop hours and refund policies?"
- Test the memory-aware chatbot: "My name is Alice" then later ask "What is my name?"
- Use the Quarkus Dev UI at /q/dev to inspect AI service calls and token usage
- Test an AI service method via the Dev UI prompt tester panel
- Ask the MCP-enabled step: "List the files in the project and summarize the main class"Troubleshooting Quarkus LangChain4J
Build fails with Java version error
Quarkus 3.x requires Java 17 or later. Run 'java -version' to check. If needed, install Java 21 LTS via SDKMAN: 'sdk install java 21-tem' then 'sdk use java 21-tem'.
LLM API calls fail with authentication errors
Check that quarkus.langchain4j.openai.api-key is set correctly in application.properties for the current step directory. Each step has its own config file — ensure you are editing the right one.
Port 8080 is already in use
Set an alternate port in application.properties: quarkus.http.port=8081. Or stop the other process using port 8080 before running ./mvnw quarkus:dev.
Frequently Asked Questions about Quarkus LangChain4J
What is Quarkus LangChain4J?
Quarkus LangChain4J is a Model Context Protocol (MCP) server that quarkus langchain4j workshop It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Quarkus LangChain4J?
Follow the installation instructions on the Quarkus LangChain4J GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Quarkus LangChain4J?
Quarkus LangChain4J works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Quarkus LangChain4J free to use?
Yes, Quarkus LangChain4J is open source and available under the Apache-2.0 license. You can use it freely in both personal and commercial projects.
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