by neomjs · MCP Server · ★ 3.3k
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npx neo-app@latestTaken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 3,292 |
| Forks | 247 |
| Language | JavaScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 56/100 |
| Open Issues | 252 |
| Last Updated | 2026-10-16 |
| Created | 2019-11-10 |
| Platforms | browser, mcp, node |
| Est. Tokens | ~17k |
Neo.mjs Neo.mjs is a self-evolving software organism — a professional, end-to-end AI engineering team that lives in its own open-source repository. Where the industry runs one AI agent and gets slop, Neo.mjs runs a swarm of minds from rival labs — Claude, Gemini, GPT — that read each other's reasoning through shared memory and Active Hybrid GraphRAG,
These tools work well together with neo for enhanced workflows:
Looking for a neo alternative? If you're comparing neo with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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A lightweight, rollbackable, and visual Long-Term Memory Server for MCP Agents. Say goodbye to Vector RAG and
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: