Knowledge Graph Memory
Summary
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.
Available Actions(9)
get_entity
Retrieve an entity by its name. Parameters: entity_name (string)
get_graph
Fetch the entire knowledge graph data. No parameters required.
create_entities
Add new entities to the knowledge graph. Parameters: entities (list of Entity objects)
add_observation
Add a unique observation to an existing entity. Parameters: entity (string), observation (string)
create_relation
Establish a relationship between two entities. Parameters: from_entity (string), to_entity (string), relation_type (string)
search_memory
Perform a search in the memory using a natural language query. Parameters: query (string)
delete_entities
Remove specified entities from the knowledge graph. Parameters: names (list of strings)
delete_relation
Remove a relationship between two entities. Parameters: from_entity (string), to_entity (string)
flush_memory
Clear all data from memory. No parameters required.
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