Search for entities in your knowledge graph memory using semantic meaning and vector similarity to find relevant information based on conceptual relationships.
Search your knowledge graph memory using semantic vector embeddings to find entities similar to your query, with options for hybrid search, similarity thresholds, and entity type filtering.
An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.
Enables creating, managing, analyzing, and visualizing knowledge graphs with support for multiple graph types (topology, timelines, changelogs, requirements, knowledge bases, ontologies) including node/edge management and resource association.
An implementation of persistent memory for Claude using a local knowledge graph, allowing the AI to remember information about users across conversations with customizable storage location.