Enables AI coding agents to persistently save, search, retrieve, update, link, and forget project-scoped memories through MCP tools, using local SQLite FTS5 keyword search without cloud access or telemetry.
Provides AI agents with persistent, local, and shareable project memory by storing decisions and code context in a searchable SQLite index, supporting keyword and semantic search via MCP.
Provides local, explicitly scoped memory for coding agents via MCP, storing durable project knowledge in a per-repository SQLite database with tools to record, search, and retrieve context.
Enables multiple AI agents on one machine to write, search, fetch, link, and give feedback on a shared local store of Markdown-backed facts, preferences, and conventions that persists across sessions. Memories gain confidence as different hosts confirm their use and can be distilled into denser ones, so agents stop re-discovering the same context.
Enables AI agents to save, recall, and forget persistent memories stored entirely on the local machine in SQLite, using hybrid semantic and keyword search with on-device embeddings, plus spaces and profile context injection.