No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by ahmedEid1 · MCP Server · ★ 88
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is lumen safe to install? View the security audit →
Lumen Type a one-sentence learning goal — an AI orchestrator builds you a private course in 50 seconds, a RAG tutor with citations teaches it, and you can audit every agent decision it made. Custom multi-agent system, no LangChain · public evals with the weak scores kept in · live in production -2ea44f?style=flat-square) Live demo · Eval results · Architecture · MCP server Real production recording (Groq Llama 3.3 70B). Intake trimmed 6×, the 50 s build 16× — the brief and the finishe
| Stars | 88 |
| Forks | 40 |
| Language | Python |
| Category | MCP Server |
| License | GPL-3.0 |
| Quality Score | 64.1828139675108/100 |
| Last Updated | 2026-06-07 |
| Created | 2020-11-29 |
| Platforms | docker, mcp, python |
| Est. Tokens | ~11644k |
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lumen is Lumen — learner-owned AI education platform. Tell the AI what you want to learn: it builds you a private course in ~a minute, tutors you with course-scoped RAG + citations, and lets you share, clone &. It is categorized as a MCP Server with 88 GitHub stars.
lumen is primarily written in Python. It covers topics such as agentic-ai, ai-tutor, byok.
You can find installation instructions and usage details in the lumen GitHub repository at github.com/ahmedEid1/lumen. The project has 88 stars and 40 forks, indicating an active community.
lumen is released under the GPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to lumen on Agent Skills Hub include orchestkit, MCP-PostgreSQL-Ops, AgentNexus-LangChain-FastAPI. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: