Local RAG semantic search for Obsidian with Ollama, LanceDB, and MCP

Local RAG Semantic Search for Obsidian with Ollama, LanceDB, and MCP

Enhance your Obsidian knowledge management with roowet-semantic-vault-search , an open-source tool designed for powerful, local RAG (Retrieval Augmented Generation) semantic search. This tool integrates seamlessly with your Obsidian vault, allowing you to find information based on meaning and context, not just keywords. By leveraging Ollama for local LLM inference, LanceDB for efficient vector storage, and MCP (presumably a component for managing or orchestrating these, as indicated by the tool's description), you can unlock deeper insights and more relevant search results directly within your notes.

What it Does

roowet-semantic-vault-search transforms your Obsidian vault into a semantically searchable database. It indexes your notes, converting their content into vector embeddings using a local LLM via Ollama. These embeddings are then stored and queried using LanceDB, a high-performance vector database. When you perform a search, the tool converts your query into an embedding and uses LanceDB to find the most semantically similar notes in your vault. This enables you to discover connections and information that traditional keyword searches would miss.

Key Features

• Local LLM Integration: Utilizes Ollama for running large language models locally, ensuring data privacy and offline functionality.
• Efficient Vector Database: Employs LanceDB for fast and scalable storage and retrieval of vector embeddings.
• Obsidian Vault Compatibility: Specifically designed to work with your existing Obsidian notes.
• Meaning-Based Search: Goes beyond keyword matching to understand the semantic meaning of your queries and notes.
• Open-Source: Freely available and modifiable, fostering community development and customization.

Who it's For

This tool is ideal for AI developers, researchers, and power users of Obsidian who need to manage and retrieve information from large, complex knowledge bases. If you are building AI applications that require efficient retrieval of contextually relevant data, or if you simply want to improve your personal knowledge management system with advanced semantic search capabilities, roowet-semantic-vault-search provides a robust and privacy-focused solution. It's particularly useful for those who prioritize local processing and data control.