A local-first Graph-RAG system combining ChromaDB with metadata-based graph relationships and Gemini 2.5 Flash for intelligent Q&A over Obsidian vaults, supporting MCP clients like Claude Desktop, Cursor, and Raycast.
Transforms Obsidian vaults into AI-powered knowledge bases using multi-layer RAG with advanced knowledge graph integration, enabling semantic search, entity extraction, and relationship mapping across personal notes.
Enables AI coding agents to search, read, create, update, and delete notes in a local Obsidian vault through hybrid semantic and lexical retrieval, with all embedding and vector storage running locally.
Enables AI agents to navigate, search, and rank notes in an Obsidian vault using graph relationships, providing context-aware access to knowledge without exposing raw file contents.
A local-first RAG, MCP, REST, and CLI bridge for Obsidian vaults that enables AI agents to retrieve cited knowledge from notes without uploading the vault.
