LangChain4j
The mature Java library for LLM apps: unified providers, tool calling, agents, and RAG on the JVM.
About
LangChain4j fills the gap Python-first AI tooling left behind: enterprises running on Java. It is an idiomatic Java library (not a port of LangChain) offering a unified API over 20+ LLM providers and 30+ vector stores, with tool calling including MCP support, agents, RAG, and streaming. It integrates with Quarkus, Spring Boot, Helidon, and Micronaut without assuming the Spring programming model.
Development pace is brisk and the project is past toy stage: a stable 1.x line with steady releases (1.20.x as of late 2026), streaming agent support, multimodal agents, and hybrid search. October 2026 comparisons frame it as the default for Java apps that live outside Spring Boot or need a reactive stack, versus Spring AI for Spring-native shops.
Apache-2.0 licensed with an active community. For JVM teams that want to add LLM capabilities to existing systems without a Python sidecar, this is the serious option.
What it can do
- Unified API over 20+ LLM providers and 30+ vector stores
- Tool calling with MCP support, agents, and RAG
- Streaming, multimodal agents, hybrid search
- Quarkus, Spring Boot, Helidon, Micronaut integrations
- Apache-2.0, stable 1.x release line
Setup
Add the Maven/Gradle dependency; configure a ChatModel for your provider; build chains, agents, and RAG pipelines with the fluent Java API.
Prerequisites
Java 8+ and Maven or Gradle; an LLM provider API key; JVM deployment target.
Use cases
Works with
Trust score — 9/10
Scored 9/10 (verified tier, metrics-v1). Evidence: 13,254 GitHub stars (langchain4j/langchain4j); repo pushed 2026-10-15 (same-day activity); Apache-2.0 confirmed via GitHub API; Unified providers/vector stores, MCP tool calling, agents, RAG, and stable 1.x line verified against official docs and independent 2026 comparisons. Manual review: the mature JVM option; idiomatic Java (not a LangChain port) is a genuine design advantage for enterprise adoption. License: Apache-2.0.
★ 13,254 GitHub stars
How the trust score is built
Full methodology →- Adoption · stars/downloads, log-scaled vs peers
- 8.0/10
- Maintenance · recency, releases, issue load
- 10.0/10
- Openness · license + docs
- 10.0/10
- Manual review · sanity read + red-flag check
- 9.0/10
- · 13,254 GitHub stars (langchain4j/langchain4j); repo pushed 2026-10-15 (same-day activity); Apache-2.0 confirmed via GitHub API
- · Unified providers/vector stores, MCP tool calling, agents, RAG, and stable 1.x line verified against official docs and independent 2026 comparisons
- · manual review: the mature JVM option; idiomatic Java (not a LangChain port) is a genuine design advantage for enterprise adoption
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.