Perform local semantic search across personal knowledge bases and expose the results to Claude via an MCP server.
Sponsored
Lake of Vectors empowers users to turn their personal knowledge bases into searchable, AI-ready resources. It indexes diverse data sources, including Obsidian notes, SQLite databases, and plaintext files, into a local ChromaDB vector store. This enables advanced semantic search, allowing users to discover relevant information based on meaning rather than just keywords. The tool seamlessly integrates with Claude Code as an MCP server, providing Claude with direct access to these personalized knowledge sources for more informed and contextualized interactions.
Key Features
010 GitHub stars
02MCP Server: Integrates directly with Claude Code for seamless querying
03Multiple Publishers: Crawl Markdown directories, SQLite tables, and plaintext files
04Semantic Search: Find relevant content by meaning, not just keywords
05Local Vectors: Runs entirely on your machine with sentence-transformers
06OpenAI Support: Optional OpenAI embeddings if preferred
Use Cases
01Performing semantic search over personal notes and documents to quickly retrieve relevant information.
02Integrating private knowledge bases (e.g., Obsidian vaults, personal databases) with AI assistants like Claude.
03Enhancing Claude's ability to answer questions by providing access to user-specific, context-rich information.
