agentdb-memory-patterns

Persistent memory for Claude Code agents is achieved using SQLite-backed storage with HNSW vector search. It organizes memory into structured namespaces, enabling reliable recall and cross-task reuse across sessions.

Implementing semantic vector search for agent memory uses HNSW vector search integrated with SQLite. This provides fast similarity matching to retrieve relevant stored patterns and solutions across tasks.

Yes, you can isolate memory scopes for different agents using namespace isolation. Namespaces like session, patterns, agents, and tasks provide per-agent scoping and lifecycle management to prevent cross-agent contamination and drift.

Yes, SQLite works well for storing agent memory patterns by providing structured storage alongside HNSW vector search. It supports lifecycle management and per-agent scoping to organize memory and enable scoped access.

You can store and reuse successful solutions across tasks by saving them as memory patterns with descriptive keys and context. The system uses HNSW vector search for semantic retrieval, enabling fast similarity matching for cross-task reuse.