Enables MCP-compatible AI coding tools to store and recall persistent memories across sessions and projects, with keyword and semantic search backed by a local SQLite database.
Enables AI coding agents to store, search, and recall project-specific and global memory through MCP, using local SQLite and semantic search. It also optionally supports autonomous task execution powered by the same memory layer.
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.
Enables AI coding agents to read and write persistent, local-first memory over MCP, storing decisions, preferences, error patterns, research, and cross-project guidelines in SQLite with semantic search. Agents can recall relevant context before tasks and store new learnings mid-session, keeping knowledge across sessions and projects without any external API calls.
Enables AI coding agents to maintain a private, local-first persistent memory by automatically saving, searching, and retrieving structured project memories through MCP, with hybrid keyword and embedding search, feedback-driven ranking, and no cloud dependency.