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…
Is LangChain4j safe? Promising trust profile, but some evidence still deserves review.
Compare LangChain4j
How does it stack up against its Agent Frameworks neighbours?
Pick any agent to compare →In detail: LangChain4j scores 66.5/100 (Grade B), ranked #468 of 1378 tracked open-source AI agent projects, on evidence coverage C (2 of 5 independent signal types). The public evidence: no package-provenance attestation found; OSSF Scorecard rates its supply-chain practices 6.3/10; 81% of recent commits are signed; last pushed 2026-10-21. Every point is earned from checkable signals — never paid placement. How scoring works →
How LangChain4j could raise its score
Each line changes one public signal and recomputes with the live scoring function. The gains don't add up exactly, because the score is capped near the top.
- Raise the OSSF Scorecard from 6.3 to 9.0lowest checks: CII-Best-Practices 0, Fuzzing 0, SAST 0 +5.6 → 72.1 B · #23 of 130
- Sign every commit81% signed today +1.0 → 67.5 B · #36 of 130
Chain of custody
Scanners check what the code says. This traces who ships LangChain4j and whether that has changed: from the source repository, through how changes are reviewed and released, to the code you run. These are the checks for OWASP ASI04 Agentic Supply Chain Vulnerabilities.
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Source Signed
github.com/langchain4j/langchain4j, Apache-2.0, last pushed 2026-10-21. 81% of the last 100 commits carry a verified signature, so changes trace to a verified account.
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Review and release Mixed
OpenSSF Scorecard rates the repository's practices 6.3/10 (scanned Oct 14, 2026). The checks that decide who can get a change released:
- Code Review2
- Branch Protection8
- Signed Releasesn/a
- Dangerous Workflow10
- Token Permissions0
- Pinned Dependencies10
All 18 Scorecard checks
Binary-Artifacts 9Branch-Protection 8CI-Tests 10CII-Best-Practices 0Code-Review 2Contributors 10Dangerous-Workflow 10Dependency-Update-Tool 10Fuzzing 0License 10Maintained 10Packaging 10Pinned-Dependencies 10SAST 0Security-Policy 10Signed-Releases -1Token-Permissions 0Vulnerabilities 0 -
Published packages None
No registry package. LangChain4j is used from its repository, so what you run is whatever you check out: pin a release tag or commit.
Changes to this chain
- 2026-09-10 OSSF Scorecard: 6.6/10
Evidence behind this score
Coverage C: 2 of 5 independent evidence types found.
- GitHub repository data
- Package downloads (missing)
- Supply-chain checks
- Public actions (missing)
- Community mentions (missing)
Verify this score yourself
Every build re-issues LangChain4j’s score as an Ed25519-signed credential, valid for 7 days. You can check it offline against HVTracker’s published key; if anyone changes a number after signing, verification fails.
What this score doesn’t check
It covers who ships the code, not what the code does. It doesn’t read tool descriptions or prompts for injected instructions, watch runtime behaviour, or find bugs nobody has disclosed yet. For that, run a content scanner before you connect it, such as Cisco MCP Scanner or Snyk Agent Scan.
How LangChain4j compares in Agent Frameworks
- #37 Astrid 67.1 +0.6
- #38 PraisonAI 67.0 +0.5
- #39 LangChain4j 66.5 this agent
- #40 VoltAgent 66.3 −0.2
- #41 Semantic Kernel 66.2 −0.3
Bars show each HVTrust score; the tick marks LangChain4j’s 66.5.
Where the 66.5 comes from
HVTrust dimensions vs the Agent Frameworks average
66.5 / 100 · 100.0% confidenceLangChain4j Agent Frameworks average (130 agents)
Quick Trust Read
How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption. Grade B reflects the trust score band: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Evidence coverage C is separate — it grades how many independent signal types back the score (2 of 5), so a high score on thin evidence stays visible. Full methodology →
Rank Trend
Activity & Reach
Analysis
Activity Inputs
90.6 / 100Common questions about LangChain4j
Does LangChain4j publish package provenance?
Does LangChain4j have an OpenSSF Scorecard?
Is LangChain4j actively maintained?
What license does LangChain4j use?
Are LangChain4j's commits signed?
Not a safety endorsement. HVTracker describes what public signals show, not whether a project is safe for your use case. Run your own security review before adopting in production.
AI agent surface
MCP, providers, tool surface
These runtime-trust fields — detected from public repo docs and manifests — contribute a bounded adjustment to this project's HVTrust score alongside supply-chain evidence. The exact values each field can add or subtract are documented in the methodology → Compare this surface across every listed agent in the capability matrix →
- MCP signal live
- External deps live
- Tool / plugin surface live
- Package provenance drift live
Detected changes to LangChain4j's runtime surface and supply-chain posture, from daily public-signal snapshots. A change here means our detectors see something different — a genuinely changed capability, or better evidence of an existing one.
Maintain LangChain4j?
For maintainers
HVTrust scores LangChain4j from public signals only — we never contact maintainers first. If a signal is wrong, stale, or missing (provenance you publish, a Scorecard you run, signed releases), tell us and we'll review it. Corrections are public and tracked on GitHub.
Reputation Timeline
Signal history
Embed Badge Badge guide for maintainers →
For maintainers
[](https://hvtracker.net/agents/langchain4j)
<a href="https://hvtracker.net/agents/langchain4j"><img src="https://hvtracker.net/badge/langchain4j.svg" alt="HVTrust"></a>
Other agents in Agent Frameworks
GitHub REST API (repo, commits, stars, forks, license) · OpenSSF Scorecard CLI
Each agent's signals refresh once daily across 6 staggered batches. Methodology v4.4 · Raw JSON