This Memory MCP Server, developed by estav, provides a knowledge graph management system for AI assistants using the Model Context Protocol. It offers tools for storing, retrieving, and querying information in a graph structure, enabling assistants to build and maintain long-term memory. The server uses SQLite for persistent storage and implements optimized batch operations for efficiency. By connecting AI capabilities with structured knowledge representation, this implementation allows assistants to accumulate and reason over information across conversations. It is particularly useful for applications requiring context retention, relationship modeling between concepts, or any scenario where an AI system needs to build and leverage a persistent knowledge base.
Retrieve an entity by its name. Parameters: entity_name (string)
Fetch the entire knowledge graph. No parameters required.
Create new entities in the graph. Parameters: entities (array of Entity objects)
Add a unique observation to an entity. Parameters: entity (string), observation (string)
Establish a relation between two entities. Parameters: from_entity (string), to_entity (string), relation_type (string)
Search for entities or observations in memory using a natural language query. Parameters: query (string)
Remove entities from the graph by their names. Parameters: names (array of strings)
Delete an existing relation between two entities. Parameters: from_entity (string), to_entity (string)
Clear all memory data. No parameters required.
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