QVAC-MCP — shared MCP for Decentralized AI Hackathon (TryDojo / ISD Summit 2026)

Shared Model Context Protocol server used across all 4 track projects + main repo. Stack: Python + FastMCP + UV. Inference rule: QVAC on-device / P2P only, never cloud.

Proposed toolset (shared across projects)

#	Tool	Why (hackathon use)
1	`qvac_docs_fetch(url)`	Crawl/research live QVAC docs (`docs.qvac.tether.io`, `qvac.tether.io`). Every project needs correct on-device API usage for Technical 35%.
2	`qvac_capability_guide(task)`	Returns minimal working snippet + model hint for a task: text-generation, embeddings, rag, transcription, translation, tts, ocr, vision, image-generation, classification, fine-tuning. Avoids hallucinated APIs.
3	`qvac_compliance_check(design_notes)`	Static check: flags `openai/chat/completions`, cloud URLs, API keys in inference path. DISQUALIFICATION guard (Art. 10). Pass = on-device/P2P only.
4	`track_brief(which)` / `track_detail(which)`	Returns parsed brief for `track1`, `track2` (Psy models on edge), `general` (main challenge, alias `main`) + rules digest so every agent plans with right context.
5	`hackathon_plan(track, idea)`	Returns a 48h plan template weighted by jury criteria (Technical 35 / Innovation 25 / Impact 20 / Design 10 / Completion 10) + deliverables checklist (repo + 5-min ES video).
6	`judge_feedback(design_notes)`	Self-critique prompt enforcing jury weights + disqualification rules before coding.

Skills exposed as resources: skill://planner, skill://builder, skill://reviewer — same behaviour in all repos.

Run

uv sync
uv run python main.py          # stdio (for agents)
uv run python main.py --http   # Streamable HTTP on :8000