Provides LLMs with direct access to official vendor PDF documentation for electronics components (TI, ST, ADI) via a local SQLite full-text index and PDF retrieval 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.
Indexes local documents (PDF, Word, Markdown, text) into a SQLite database for AI agents to search and retrieve bounded, source-located passages. Runs fully locally with optional OCR, preserving privacy.
Enables semantic search and conversational querying across a personal research library of PDFs, DOCX, and other documents using a vector database. It provides tools for document summarization, finding related papers, and high-accuracy retrieval for AI clients like Claude Desktop.
Provides fast, token-efficient search over coding agent documentation (e.g., Claude Code, Cursor) using local SQLite FTS5 indexing, with tools for searching snippets, reading pages, and grepping markdown.
Builds searchable SQLite databases from PDFs, preserving inline image locations for AI agents to discover and caption visual content. Supports full-text search over text, image placeholders, and saved captions.