Knowledge Graph
Summary
Knowledge Graph Memory Server provides persistent memory for Claude through a local knowledge graph, allowing the AI to remember information across conversations. Developed by itseasy21 as a fork of the original Memory Server, it stores data as entities with observations and relations between them, enabling structured information retrieval and complex knowledge representation. The implementation supports customizable memory paths, cross-platform compatibility, and offers a comprehensive API for creating, updating, and querying graph elements, making it ideal for personalized chat experiences where context retention is essential.
Available Actions(9)
create_entities
Create multiple new entities in the knowledge graph. Input: entities (array of objects) containing name (string), entityType (string), and observations (string[]). Ignores entities with existing names.
create_relations
Create multiple new relations between entities. Input: relations (array of objects) with from (string), to (string), and relationType (string). Skips duplicate relations.
add_observations
Add new observations to existing entities. Input: observations (array of objects) with entityName (string) and contents (string[]). Returns added observations per entity, fails if entity doesn't exist.
delete_entities
Remove entities and their relations. Input: entityNames (string[]). Performs cascading deletion of associated relations, silent operation if entity doesn't exist.
delete_observations
Remove specific observations from entities. Input: deletions (array of objects) with entityName (string) and observations (string[]). Silent operation if observation doesn't exist.
delete_relations
Remove specific relations from the graph. Input: relations (array of objects) with from (string), to (string), and relationType (string). Silent operation if relation doesn't exist.
read_graph
Read the entire knowledge graph. No input required. Returns complete graph structure with all entities and relations.
search_nodes
Search for nodes based on query. Input: query (string). Searches across entity names, entity types, and observation content. Returns matching entities and their relations.
open_nodes
Retrieve specific nodes by name. Input: names (string[]). Returns requested entities and relations between them, silently skips non-existent nodes.
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