NomaDamas/MinSync

A minimal Python package for storing and retrieving text using chunking, embeddings, and vector search.

mini cli search engine for your docs, knowledge bases, meeting notes, whatever. Tracking current sota approaches while being all local

Local-first RAG MCP server in Python: hybrid search (semantic + BM25 keyword boost) over your own documents. 11 MCP tools + CLI, markitdown ingestion for 12 formats, multilingual embeddings, LanceDB. Nothing leaves your machine.

Local RAG server for Claude Code, Cursor and other MCP clients: hybrid BM25 + vector search with cross-encoder reranking on by default, 13 MCP tools, 33 file types including code, re-indexing on file changes. One Python process with embedded ChromaDB and FastEmbed ONNX: no Docker, database server or API key; offline after the first model download.

Language model search engine built on a vector database and an anything key/value store.

Two-tier hybrid local search for Rust and the fsfs CLI: sub-millisecond first-pass results from a Potion/Model2Vec fast tier, then MiniLM quality refinement. Fuses native pure-Rust BM25 (Quill engine) and semantic vector search with Reciprocal Rank Fusion. Progressive iterator API, f16 SIMD vector index, feature-gated compilation.

Find your files with natural language and ask questions.

A lightweight CLI tool for RAG over local documents

Vector Storage is a vector database that enables semantic similarity searches on text documents in the browser's local storage. It uses OpenAI embeddings to convert documents into vectors and allows searching for similar documents based on cosine similarity.