LibreChat vs Neo
Neo leads on trust: 90.3/100 (Grade A) against 73.5/100 (Grade B), a 16.8-point gap. LibreChat leads on adoption and rests on broader evidence; Neo leads on supply-chain integrity and provenance. Note: Neo's evidence coverage is thinner (coverage B vs A) — its score rests on fewer independent signal types.
Enhanced ChatGPT Clone: Features Agents, MCP, Skills, DeepSeek, Anthropic, AWS, OpenAI, Responses API, Azure, Groq, o1, GPT-5, Mistral, OpenRouter, Vertex AI, Gemini, Artifacts, AI model switching, message search, Code Interpreter, langchain, DALL-E-3, OpenAPI Actions, Functions, Secure Multi-User…
Choose LibreChat if adoption matters most.
- +5.0Adoption: 637.5k weekly downloads against 11.9k
- A vs BEvidence coverage: 4 of 5 independent signal types, against 3
Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active Hybrid GraphRAG, DreamService, and self-healing loops.
Choose Neo if supply-chain integrity and provenance matter most.
- +9.5Safety / Integrity: OSSF Scorecard 6.6 against 5.0
- +7.2Identity / Provenance: package provenance attested, against none
- +1.3Transparency: OSSF Scorecard 6.6 against 5.0
Where they differ
1 dimension identical: Maintenance 19.9 · Full evidence table
An independent, evidence-based trust comparison of LibreChat and Neo, two UI & App Builders projects in the HVTracker registry. Scores come from public, checkable signals — supply-chain provenance, OSSF Scorecard, maintenance, and adoption — not popularity.
Full evidence
| Signal | LibreChatLibreChat-AI/LibreChat | Neoneomjs/neo |
|---|---|---|
| HVTrust score | 73.5 | 90.3 |
| Evidence grade | B | A |
| Coverage grade | A | B |
| Overall rank | #289 | #23 |
| Rank in UI & App Builders | #6 | #1 |
| GitHub stars | 46.7k | 3.3k |
| Last updated | 1d ago | 1d ago |
| Build provenance | No | Yes |
| OSSF Scorecard | 5.0 / 10 | 6.6 / 10 |
| License | MIT | MIT |
| Downloads | 637k/wk | 12k/wk |
| Trust dimensions (points earned) | ||
| Safety / integrity / 25 | 11.2 | 20.7 |
| Identity & provenance / 18 | 10.8 | 18.0 |
| Transparency / 17 | 12.8 | 14.1 |
| Maintenance / 20 | 19.9 | 19.9 |
| Adoption / 20 | 18.9 | 13.9 |
| Runtime capability surface (full matrix) | ||
| MCP server | Implemented | Implemented |
| External providers | 4 — Anthropic, Google Gemini, OpenAI, … | — |
| Requires API keys | No | No |
| Plugin surface | plugins | plugins |
| Provenance drift | — | Match |
How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption, scaled by an evidence-confidence factor. Grade bands: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Signals refresh daily. Full methodology v4.4 →