AI-first learning platform with a tutor grounded in the course itself, multi-modal authoring, and verifiable credentials — FastAPI + Next.js, Groq Llama 3.3 70B, MCP server, golden eval suite. Live demo at lumen.ahmedhobeishy.tech.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"e-learning-platform": {
"command": "<see-readme>",
"args": []
}
}
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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.
This server supports HTTP transport. Be the first to test it — help the community know if it works.
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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
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 finished course are real-time.
Try it yourself: the one-click demo pre-fills demo@lumen.test / Demo!2026 and drops you into the tutor (free-tier box — give a cold page a few seconds).
A learner-owned, two-role e-learning platform — every signed-in user runs the whole loop themselves; admin only moderates and configures. The product is the loop; the point of the repo is the agentic system underneath it.
| Step | What happens |
|---|---|
| Define | A guided AI intake (capped at six turns) turns a fuzzy goal into a structured learning brief — the source goal is field-encrypted at rest |
| Build | The authoring orchestrator builds a private course from the brief — honest status, no half-finished partials, re-runnable, cancellable (build.py, the durability/idempotency/quota shell) |
| Learn | A course-scoped RAG tutor answers with lesson citations and a visible tool-call trace |
| Share | Publishing stays private; public listing is an explicit share + admin moderation state machine with an immutable audit trail |
| Clone | Any listed course can be remixed into your own draft, with server-written "Based on …" provenance and a sanitized export (no enrollments, traces, or soft-deleted content) |
| BYOK | Bring your own model key (OpenAI / Anthropic / Groq / Mistral) — allowlisted providers, server-owned base URLs, envelope-encrypted write-only keys |
Shipped to production as 2.0.0-two-role (CHANGELOG) — built as a gated waterfall: requirements → design → 6 ADRs → seven build streams, each cleared a Codex challenge, an independent Claude review, and a live in-browser walk before merge.
Every item below is on production today, with the code one click away.
The tutor picks per-turn among five sub-agents in tutor_subagents/ — retriever, web_searcher, code_runner, quiz_generator, concept_explainer — under a hard cap on tool-call rounds (streaming variant). The authoring side runs a six-stage pipeline — researcher → outliner → critic → reviser → lesson-drafter → final-critic — in authoring_orchestrator.py, capped at six revise/critic calls.