The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the MCP Knowledge Gaps listing page.
Find what your knowledge base mentions but doesn't actually explain.
Find concepts mentioned but never defined in your markdown knowledge base (Obsidian vault, Logseq graph, any folder of .md files). Uses fuzzy canonicalization to avoid false positives, ranks gaps by frequency × region-diversity × novelty, generates prioritized research questions, and samples from the long tail via sortition to break confirmation bias in your research queue.
Add to claude_desktop_config.json:
| Tool | Tier | Description |
|---|---|---|
find_gaps | Free | Scan a markdown vault and return concepts mentioned in multiple notes but without their own dedicated note. Applies fuzzy canonicalization and noise filtering. |
list_gaps_by_priority | Free | Return gaps ranked by priority: frequency × diversity × novelty (higher = fill this gap first). |
generate_research_questions | Pro | Generate prioritized research questions for the top N gaps. Each question comes with a priority score and factor breakdown. |
surprise_research_topic | Pro | Sortition sampling — pick a random gap from the LOW-priority long tail. Breaks confirmation bias by surfacing topics you'd never pick yourself. |
export_review_queue | Pro | Export a CSV of top-priority gap concepts, suitable for Anki or other spaced-repetition tools. Writes to output_csv and returns the row count. |
Unlocks research question generation with RL-weighted ranking, sortition sampling of long-tail gaps, and CSV review queue export.
License activation — any one of these works:
Licenses are verified fully offline — no phone-home, no activation server. Get a license at https://github.com/onetrueclaude-creator/mcp-knowledge-gaps#pro-tier.
MIT