openclaw-memory

Persistent AI memory across sessions prevents context resets by storing conversation data locally. You can save context using a command like 'claw memory add' to retain facts and preferences for future interactions without repeating prompts.

Semantic search retrieves stored conversation memories by matching meaning rather than exact keywords. This mechanism allows quick recall of relevant facts, user preferences, and patterns automatically extracted from past sessions.

Local storage for AI agent memory is supported on Node.js. The system installs via 'claw skill install openclaw-memory', running locally to persist extracted facts and preferences while integrating session-end hooks for data retention.

Automatic extraction of facts and preferences from AI conversations is handled by integrating request-before, request-after, and session-end hooks. This approach continuously captures user patterns from active chats into persistent local storage.

You need x402 agent payments to unlock unlimited AI memory retention via the Pro tier upgrade. This payment protocol enables permanent memory storage, whereas the base tier provides standard local memory capacity.

An AI agent forgets context after a session ends because it lacks persistent memory storage. Installing a memory skill with session-end hooks ensures extracted conversation patterns and facts are saved locally for retrieval in subsequent interactions.