Enables persistent, portable memory for AI agents across sessions, devices, and providers with token-efficient 5-level lazy loading and automatic session capture.
Enables persistent, graph-based memory for AI agents, allowing them to store, traverse, and recall relationships between facts, decisions, and context across sessions for efficient reasoning and reduced token usage.
Persistent, compact project memory for AI coding agents, enabling them to read a small digest instead of re-scanning the codebase every session, saving tokens and costs.
Persistent long-term memory for AI agents via MCP, saving 80-90% memory-related token costs by enabling on-demand recall instead of always-injecting context.