mcp-knowledge-gaps

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.

Install

pip install mcp-knowledge-gaps
# or
uvx mcp-knowledge-gaps

Usage

Claude Code

claude mcp add mcp-knowledge-gaps -- mcp-knowledge-gaps

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "knowledge_gaps": {
      "command": "uvx",
      "args": ["mcp-knowledge-gaps"]
    }
  }
}

MCP Tools

Pro tier

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:

# 1. Environment variable
export KNOWLEDGE_GAPS_LICENSE="eyJhbGc..."

# 2. CLI flag
mcp-knowledge-gaps --license-key "eyJhbGc..."

# 3. Config file
echo "eyJhbGc..." > ~/.mcp-knowledge-gaps/license.jwt

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.

Requirements

• Python 3.10+

License

MIT