News
- Spring AI 2.0.0-M4, 1.1.4, and 1.0.5 Available — JSpecify null-safety completion, new features, and maintenance releases
- Introducing Tracy: The AI Observability Library for Kotlin — production-grade AI observability with OpenTelemetry
- Multi-Language MCP Server Performance Benchmark — comparative analysis across Go, Java, Python, and TypeScript
- 2026 Java AI Apps — building AI applications with Java in 2026
- Agent Memory Is Not a Greenfield Problem — ground it in your existing data
- Production LangChain4j at Devoxx Belgium — advanced RAG, agentic workflows, and production tips
Agent Frameworks & Libraries
15 entriesSpring AI
The Spring ecosystem's official AI framework. Portable abstractions across 20+ model providers, tool calling, RAG, chat memory, vector stores, and MCP support. Built by the Spring team at Broadcom.
LangChain4j
The most popular Java LLM library. Unified API across 20+ LLM providers and 30+ embedding stores. Three levels of abstraction from low-level prompts to high-level AI Services. Supports RAG, tool calling, MCP, and agents.
Embabel
Created by Rod Johnson (Spring Framework creator). JVM agent framework using Goal-Oriented Action Planning (GOAP) for dynamic replanning. Strongly typed, Spring-integrated, MCP support. Written in Kotlin with full Java interop.
Google ADK for Java
Google's Agent Development Kit — code-first Java toolkit for building, evaluating, and deploying AI agents. Supports Gemini natively plus third-party models via LangChain4j. A2A protocol for agent-to-agent communication.
Quarkus LangChain4j
Enterprise-grade Quarkus extension for LangChain4j. Native compilation with GraalVM, built-in observability (metrics, tracing, auditing), and Dev UI tooling. Maintained by Red Hat & IBM.
LangChain4j CDI
CDI extension for LangChain4j that brings AI services to Jakarta EE and MicroProfile applications. Inject AI services as CDI beans with @RegisterAIService. Supports Quarkus, Helidon, WildFly, Payara, GlassFish, Liberty, and any CDI-capable runtime.
LangGraph4j
Build stateful, multi-agent applications with cyclical graphs. Inspired by Python's LangGraph, works with both LangChain4j and Spring AI. Persistent checkpoints, deep agent architectures, and a Studio web UI.
Koog (JetBrains)
Kotlin-native agent framework from JetBrains. Type-safe DSL, multiplatform (JVM, JS, WasmJS, Android, iOS), A2A protocol support, fault tolerance with persistence, and multi-LLM support.
Semantic Kernel (Java)
Microsoft's AI orchestration SDK with Java support. Merged with AutoGen into a unified Microsoft Agent Framework with deep Azure integration. Supports prompt chaining, planning, and memory.
MCP Java SDK
The official Java SDK for Model Context Protocol servers and clients. Co-maintained by the Spring AI team and Anthropic. Sync/async, STDIO/SSE/Streamable HTTP transports, OAuth support.
Anthropic Java SDK
Official Java SDK for the Claude Messages API. Streaming, retries, structured outputs, extended thinking, code execution, and files API. Build Java apps powered by Claude.
GitHub Copilot SDK for Java
Official Java SDK for embedding the GitHub Copilot agentic engine directly into Java applications. Exposes planning, tool calling, file editing, and MCP integration via a simple Java API. Currently in technical preview.
Tracy (JetBrains)
AI tracing library for Kotlin and Java. Captures structured traces from LLM interactions — messages, cost, token usage, and execution time. Implements OpenTelemetry Generative AI Semantic Conventions.
Docling Java
Official Java client and tooling for Docling — converts messy documents into structured data. Detects tables, formulas, reading order, OCR, and simplifies downstream AI processing.
OmniHai
Unified Java AI utility library for Jakarta EE and MicroProfile. Single API across 10+ providers with zero external runtime dependencies — just java.net.http.HttpClient. Chat, streaming, structured outputs, web search, translation, moderation, image/audio generation, and more in a ~210 KB JAR.
Java with Code Assistants
MCP servers, skill registries, and IDE integrations that bridge AI assistants and the Java ecosystem.
Javadocs.dev MCP Server
Gives AI assistants live access to Java, Kotlin, and Scala library documentation from Maven Central. Six tools including latest-version lookup, Javadoc symbol browsing, and source file retrieval. Connect any MCP client via Streamable HTTP.
JetBrains AI
AI-powered coding assistance built into IntelliJ IDEA and all JetBrains IDEs. Context-aware code completion, next-edit suggestions, and an agent-mode chat for refactoring, test generation, and complex tasks. Supports cloud LLMs plus bring-your-own-key.
SkillsJars
A packaging format and registry for distributing reusable AI agent skills as Maven/Gradle JARs. Skills are Markdown files (SKILL.md) under META-INF/skills/ that teach AI agents domain-specific patterns. Discover and load skills on demand in Claude Code, Kiro, and Spring AI apps.
Inference & Training
Run models, train classifiers, and do ML inference directly on the JVM — no Python required.
Jlama
Modern LLM inference engine written in pure Java. Runs Llama, Gemma, Mistral, and more locally on CPU. Uses Java's Vector API (Project Panama) for SIMD-accelerated matrix math. Supports GGUF and SafeTensors formats, quantized models, and distributed inference.
Deep Java Library (DJL)
AWS's high-level, engine-agnostic deep learning framework. Supports PyTorch, TensorFlow, and MXNet backends. Used in production at Netflix and Amazon for real-time inference. DJLServing provides high-performance model serving.
ONNX Runtime Java
Run transformer and classical ML models directly on the JVM. Hardware acceleration via CUDA, ROCm, DirectML, and more. Enables deploying scikit-learn, PyTorch, and HuggingFace models in Java without Python or REST wrappers.
Tribuo
Oracle Labs' ML library for classification, regression, clustering, and anomaly detection. Strong typing, provenance tracking for reproducibility, and integrations with XGBoost, ONNX Runtime, TensorFlow, and LibSVM.
GPULlama3.java
First Java-native Llama 3 implementation with automatic GPU acceleration via TornadoVM. No CUDA or native code needed — GPU-accelerated LLM inference in pure Java. From the University of Manchester's Beehive Lab.
TensorFlow Java
Official Java bindings for TensorFlow. Train and deploy TF models entirely in Java. Used by Tribuo under the hood. Suitable for teams that want to stay within the JVM ecosystem while using TensorFlow's model formats.
People to Follow
Key voices at the intersection of Java and AI
Content, Communities & Resources
- Community Java Conferences Tracker — community-maintained calendar of all Java conferences worldwide
- Blog Java Relevance in the AI Era — RedMonk analysis of Java's position as agent frameworks emerge
- Resource Awesome Spring AI — curated list of Spring AI resources, tools, and tutorials
- Book Spring AI in Action (Manning) — by Craig Walls, comprehensive guide to building AI apps with Spring
- Resource Production LangChain4j — Inside.java — advanced RAG, agentic workflows, and production tips from Devoxx Belgium
- Resource Google ADK Java Codelab — hands-on: build AI agents in Java with Google's ADK
- Video Devoxx YouTube — thousands of conference talks on Java, AI, cloud, and architecture
- Video Coffee + Software — Spring ecosystem, AI integration, and Java community
- Podcast Foojay Podcast: Java AI Revolution — agents, MCP, graph databases — developers navigate the AI revolution
- Workshop Building Java AI Agents with Spring AI (AWS) — hands-on workshop including deployment to EKS
- Livestream AI & Java on Serverless Office Hours — MCP integration, agent architectures, GraalVM optimization