AI Note Searcher 5000

Example Use Cases

• 1

  Perform semantic search over personal Obsidian note collections.

• 2

  Integrate intelligent note retrieval via MCP protocol with LLMs.

• 3

  Real-time updates and hybrid search combining vector similarity and full-text matching.

Description

AI Note Searcher 5000 is a dockerized semantic search system designed specifically for Obsidian notebooks. It watches your note folder in real-time, generates vector embeddings using Ollama, stores them in Qdrant, and exposes a Model Context Protocol (MCP) server for LLM integration. This enables intelligent, hybrid semantic and full-text search with metadata support, improving note retrieval and management.