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MCP server · AI

Langchain4j

LangChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It offers a unified API over popular LLM providers and vector stores, and makes implementing tool calling (including MCP support), agents and RAG easy. It integrates seamlessly with enterprise Java frameworks like Quarkus and Spring Boot.

Unclaimed Apache-2.0 agentic-aimcprag
92Excellent

Scored 8 days ago · breakdown

About Langchain4j

Langchain4j is an MCP server published by langchain4j in the AI category: langChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It offers a unified API over popular LLM providers and vector stores, and makes implementing tool calling (including MCP support), agents and RAG easy. It integrates seamlessly with enterprise Java frameworks like Quarkus and Spring Boot.

The repository has 13K stars and 2.7K forks, with the last commit 2 days ago. Recent commit activity is the strongest signal that reported issues will get attention.

Install

From source
git clone https://github.com/langchain4j/langchain4j

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Security checks

Static checks derived from the repository yesterday. Heuristics on the source, not an audit.

  • ✓README presentThe repository ships documentation.
  • ✓License declaredUsable under a stated license.
  • ✓Tests presentA test suite exists in the repository.
  • ✓Dependencies pinnedA lockfile pins dependency versions.
  • !No dynamic code executionSource scan found eval or shell execution. Review how tool inputs reach it before granting credentials.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

Releases

1.22.01.22.0 and 1.22.0-beta32 · 8 Oct 2026Notable Changes Decision Models: Add OpenAI Decisions API support: OpenAiDecisionModel and OpenAiOfficialDecisionModel by @dliubarskyi in https://github.com/langchain4j/langchain4j/pull/6611 Decision Services: images as parameters, and…
1.21.01.21.0 and 1.21.0-beta31 · 2 Oct 2026Decision Models (experimental) This release introduces decision models: a new model type that answers questions about an input with typed answers and probabilities instead of generated text. They are a fast, cheap fit for classification,…
1.20.21.20.2 and 1.20.2-beta30 · 28 Sep 2026A2a fixes (#6512) Full Changelog: https://github.com/langchain4j/langchain4j/compare/1.20.1...1.20.2
1.20.11.20.1 and 1.20.1-beta30 · 25 Sep 2026What's Changed Allow methods annotated with @McpClientSupplier to also have supplier parameters by @mariofusco in https://github.com/langchain4j/langchain4j/pull/6505 Full Changelog:…
1.19.31.19.3 and 1.19.3-beta29 · 15 Sep 2026What's Changed Allow to configure ClassLoader on the ObjectMapper used for AgenticScope serialization by @mariofusco in https://github.com/langchain4j/langchain4j/pull/6409 1.19 mcp backports by @jmartisk in…

README

LangChain4j: idiomatic, open-source Java library for building LLM-powered applications on the JVM

Build Status Nightly Build CODACY

Discord BlueSky X Maven Version

Introduction

Welcome!

The goal of LangChain4j is to simplify integrating LLMs into Java applications.

Here's how:

  1. Unified APIs: LLM providers (like OpenAI or Google Vertex AI) and embedding (vector) stores (such as Pinecone or Milvus) use proprietary APIs. LangChain4j offers a unified API to avoid the need for learning and implementing specific APIs for each of them. To experiment with different LLMs or embedding stores, you can easily switch between them without the need to rewrite your code. LangChain4j currently supports 20+ popular LLM providers and 30+ embedding stores.
  2. Comprehensive Toolbox: Since early 2023, the community has been building numerous LLM-powered applications, identifying common abstractions, patterns, and techniques. LangChain4j has refined these into practical code. Our toolbox includes tools ranging from low-level prompt templating, chat memory management, and function calling to high-level patterns like Agents and RAG. For each abstraction, we provide an interface along with multiple ready-to-use implementations based on common techniques. Whether you're building a chatbot or developing a RAG with a complete pipeline from data ingestion to retrieval, LangChain4j offers a wide variety of options.
  3. Numerous Examples: These examples showcase how to begin creating various LLM-powered applications, providing inspiration and enabling you to start building quickly.

LangChain4j began development in early 2023 amid the ChatGPT hype. We noticed a lack of Java counterparts to the numerous Python and JavaScript LLM libraries and frameworks, and we had to fix that!

Despite the name, LangChain4j is not a Java port of LangChain (Python) — it is built for Java, not ported to it. It is an idiomatic Java library designed from the ground up around Java conventions: type safety, POJOs, annotations, interfaces, dependency injection, fluent APIs, and first-class integrations with Quarkus, Spring Boot, Helidon, and Micronaut. Its API, internals, and release cycle are independent of the Python LangChain project.

We actively monitor community developments, aiming to quickly incorporate new techniques and integrations, ensuring you stay up-to-date. The library is under active development. While some features are still being worked on, the core functionality is in place, allowing you to start building LLM-powered apps now!

Documentation

Documentation can be found here.

The documentation chatbot (experimental) can be found here.

Getting Started

Getting started guide can be found here.

Code Examples

Please see examples of how LangChain4j can be used in langchain4j-examples repo:

Useful Materials

Useful materials can be found here.

Get Help

Please use Discord or GitHub discussions to get help.

Request Features

Please let us know what features you need by opening an issue.

Contribute

Contribution guidelines can be found here.

README fetched from the repository yesterday. The original is authoritative.

Questions

About Langchain4j

How do I install Langchain4j?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Langchain4j safe to use with an AI agent?

Its trust score is 92 out of 100 (excellent). It passes 4 of the 6 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Langchain4j still maintained?

Yes — the latest release is 1.22.0 (8 Oct 2026), and the last commit was 2 days ago. The repository has 13K stars and 1011 open issues.