Enables semantic search across personal PDF paper collections with page-level citations, allowing users to query their library from any MCP-capable client.
Enables creation and management of academic-paper knowledge bases from PDFs, including ingestion, semantic search with reranking, and document-level retrieval via MCP tools.
A local academic research assistant that indexes PDFs into a searchable vector library and exposes MCP tools for semantic search, claim extraction, contradiction detection, and multi-step research synthesis.
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.
Enables semantic search over a personal document corpus through MCP tools, allowing users to retrieve ranked chunks, access full document context, and list sources from their semester notes.