kb-memory

Persistent preferences are stored using a knowledge graph that maps stable user settings and entity relationships. This ensures the AI applies your specific interaction formats automatically without requiring repeated manual input.

Knowledge graph memory for entity mapping is a structured storage method that links people, roles, and projects. It allows the system to retrieve relationship context dynamically, ensuring accurate and personalized data recall during interactions.

You create and retrieve pointers to knowledge base notes by triggering memory operations through specific keywords. The system uses an MCP server to manage these nodes, avoiding data duplication by linking to existing notes.

Yes, knowledge graph memory works without duplicating data by storing pointers to relevant KB notes rather than the content itself. It creates nodes and observations that reference existing information to avoid redundancy.

You trigger remembering or forgetting information in a knowledge graph by using specific keywords related to memory operations in your queries. The system then executes the corresponding create or delete actions on the stored nodes.

Yes, you can use MCP server-memory to manage persistent knowledge base nodes. It handles the operations for searching, opening, creating, and deleting nodes and observations within the knowledge graph structure.