matryca-plumber
Enables teams to maintain semantic consistency and discoverability across Markdown documentation without vendor lock-in or external API dependencies, reducin…
Local-first AI daemon for Logseq OG: background semantic indexing, link hygiene, and agent-ready CLI/MCP — edits Markdown on disk (no cloud, no Logseq API). Karpathy LLM-Wiki inspired.
- Ask Claude to automatically index and tag related notes in your Logseq vault for better discoverability.
- Generate missing backlinks between markdown documents based on semantic similarity of content.
- Automate cleanup of broken or orphaned links across your entire local knowledge base.
Enables teams to maintain semantic consistency and discoverability across Markdown documentation without vendor lock-in or external API dependencies, reducing operational risk and keeping sensitive knowledge local.
Engineering teams managing large Markdown knowledge bases who need automated link maintenance and semantic search without cloud infrastructure.
https://github.com/MarcoPorcellato/matryca-plumber
By MarcoPorcellato
How to Get It
claude plugins install MarcoPorcellato/matryca-plumber
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:
Automatically index and tag related notes in my Logseq vault for better discoverability
Trust Signals Auto-scanned
Community Pulse New
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 82 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.
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): 82 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.