Exo-Graph creates an advanced knowledge graph engine that addresses the ephemeral memory limitations of traditional LLMs. It functions as an 'exocortex' by externalizing LLM memory into a Neo4j database, ensuring knowledge persistence across sessions. The tool captures rich context through a Subject-Relationship-Object triplet structure, enhanced with metadata like summary, confidence, and temporal data. This enables powerful capabilities such as hybrid semantic and graph search, automated entity standardization, intelligent negation handling, and temporal conflict resolution, providing AI systems with a scalable, connected, and evolving memory.
主な機能
01Persistent Knowledge Storage in Neo4j
02Hybrid Semantic and Graph Search Capabilities
03Temporal Intelligence and Conflict Resolution
04Automated Entity and Relationship Standardization
050 GitHub stars
06Model Context Protocol (MCP) Integration for AI Assistants
