Provides 11 tools for stock research, including search, market history, financial statements, announcements, and data quality checks, with a local-first architecture using DuckDB and Parquet.
Provides semantic search and management of shared documentation using ChromaDB and OpenAI embeddings. It enables users to query local documents by meaning, list files, and read content through natural language tools.
Enables AI assistants to search and query PDF documents through a local RAG system with vector embeddings. Provides semantic document search capabilities while keeping all data stored locally without external dependencies.
Provides RAG search and ask capabilities over markdown and text files using Qdrant vector database, with tools for ingestion, retrieval, and source management.