Enables AI agents and MCP hosts to query locally indexed notes, docs, chat logs, and other files via hybrid vector/BM25 retrieval with section-level citations. Exposes tools, resources, and prompts for searching and asking over the indexed content.
Enables coding agents to query local notes, decisions, docs, and code with hybrid retrieval (BM25 + embeddings + reranking) and get path:line citations. It provides tools like rag_query for full-corpus search and search_knowledge for project-scoped knowledge recall.
Enables AI hosts and agents to query locally indexed notes, docs, PDFs, chat logs, and other scattered files through hybrid vector and BM25 retrieval with section-level citations. It exposes tools, resources, and prompts for searching, asking questions, scoping by tags, traversing links, and reranking results.
Enables AI agents and MCP hosts to query a local, machine-resident index of scattered notes, project docs, PDFs, Office files, and chat exports using hybrid vector + BM25 retrieval with section-level citations. Exposes tools, resources, and prompts so hosts like Claude Desktop, Cursor, and Cline can search, ask, and explore linked knowledge through natural language.
Enables AI agents and MCP hosts to run hybrid vector + BM25 retrieval over a locally indexed second brain of scattered notes, docs, PDFs, chat logs, and wiki pages, returning section-level citations. It exposes 8 tools plus resources and prompts so hosts like Claude Desktop, Cursor, Cline, and Claude Code can search and ask questions of your own files.