kaas
Consolidates fragmented documentation into a searchable, structured knowledge base without external dependencies or embedding costs, reducing institutional k…
Turn scattered notes, docs and transcripts into a queryable Markdown wiki — an LLM knowledge-base compiler with MCP access, no embeddings, self-hosted.
- Generate a searchable Markdown wiki from scattered meeting transcripts and documentation files
- Compile internal knowledge base from notes and docs without needing vector embeddings or external APIs
- Ask Claude to extract key information from multiple documents and organize into structured wiki format
Consolidates fragmented documentation into a searchable, structured knowledge base without external dependencies or embedding costs, reducing institutional knowledge silos and onboarding friction.
Engineering teams managing distributed documentation and internal wikis seeking self-hosted, low-operational-overhead knowledge management.
https://github.com/bybit-exchange/kaas
By bybit-exchange
How to Get It
claude plugins install bybit-exchange/kaas
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help me generate a searchable Markdown wiki from scattered meeting transcripts and documentation files
Trust Signals Auto-scanned
Community Pulse New
- KaaS – Knowledge as a Service: an out-of-the-box LLM wiki compiler — Hacker News · 2 pts
1 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 64 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Evaluation
Scored from trust signals (evidence-eval-v1): 64 GitHub stars; contributors unknown; last commit 0d ago; license MIT.