RAG-powered document search server that enables semantic search across large collections of legal and business documents (PDF, Word, Excel, PowerPoint) using local embeddings with no API costs.
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process.env. You'll be asked to provide them before it can run.HF_HUB_DISABLE_SYMLINKS_WARNINGICKY_CHUNK_SIZE— 5000 Approximate tokens per chunkICKY_CHUNK_OVERLAP— 500 Approximate token overlap between chunksICKY_EMBEDDING_PROVIDER— Set ICKY_VOYAGE_API_KEY when using the default Voyage backend. For offline use, set =local.ICKY_LOCAL_MODEL— nomic-ai/nomic-embed-text-v1.5 Local sentence-transformers modelICKY_VOYAGE_API_KEY— Set when using the default Voyage backend. For offline use, set ICKY_EMBEDDING_PROVIDER=local.ICKY_VOYAGE_MODEL— voyage-3.5-lite Voyage embedding modelICKY_VOYAGE_DIMENSIONS— 1024 Voyage output dimensionICKY_VOYAGE_WORKERS— 8 Reserved for parallel Voyage workflowsICKY_DATA_DIR— ./data Base directory for per-user databasesICKY_DB_PATH— provider-specific Legacy single database path[](https://m8ven.ai/mcp/dl1683-ickymcp-125lh9)