Semantic fact indexer over markdown knowledge bases — extracts atomic facts, entities, and authority scores, then exposes search via MCP
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# mcp-fact-finder Semantic fact indexer over markdown knowledge bases. Crawls markdown documents, extracts atomic facts using **local NLP (free, no API key)** or an optional LLM enrichment pass, stores facts in LanceDB with authority scoring and entity relationships, and exposes structured search via the Model Context Protocol. --- ## Why local inference? > **Pass 1 (rebel-large NLP) is completely free.** No API keys, no rate limits, no cost. Runs locally on CPU or Apple Silicon MPS (Metal Performance Shaders). A full 7,600-document knowledge base indexes in ~5 hours at $0. **Pass 2 (LLM enrichment) is optional.** It adds canonical fact forms, tense classification, and better entity linking. Use a local Ollama instance (free) or OpenRouter (~$5–9 for 7,600 docs). > **Recommendation:** Run Pass 1 first. For most knowledge bases, Pass 1 alone > is sufficient for useful search results. --- ## Status: v0.0.3 | Component | Status | |-----------------------|----------| | Data models | ✅ Complete | | Markdown crawler | ✅ Complete | | Authority scoring | ✅ Complete | | rebel-large extractor | ✅ Complete | | Ollama extractor | ✅ Complete | | OpenRouter/Bedrock | ✅ Complete | | Embedder (bge-small) | ✅ Complete | | LanceDB store | ✅ Complete | | MCP server (6 tools) | ✅ Complete | | Inconsistency checker | ✅ Complete | | Indexing pipeline | ✅ Complete | | Setup script | ✅ Complete | --- ## Quick start ### 1. Install ```bash pip install mcp-fact-finder # or uv add mcp-fact-finder ``` Or clone and develop locally: ```bash git clone https://github.com/bobmatnyc/mcp-fact-finder cd mcp-fact-finder uv sync ``` ### 2. Index your knowledge base (Pass 1 — free, no API key needed) ```bash # Index a directory of markdown files uv run scripts/index.py --path ~/my-docs/ # First 100 docs only (quick smoke test) uv run scripts/index.py --path ~/my-docs/ --limit 100 # Show current stats uv run scripts/…
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