LLM Exo-Graph Knowledge Engine

Example Use Cases

• 1

  Persistent memory beyond ephemeral LLM context windows.

• 2

  Query and update knowledge graphs with temporal and semantic intelligence.

• 3

  Integration with Neo4j for advanced graph and vector search capabilities.

Description

LLM Exo-Graph creates an exocortex by storing knowledge graph data externally in Neo4j, enabling AI assistants to have persistent, searchable memory across sessions. It supports semantic and graph-based search, temporal intelligence, negation handling, and conflict resolution, improving the reliability and scalability of AI knowledge management. The MCP server integrates via Server-Sent Events (SSE) to allow AI models like Claude to interact with the knowledge graph in real-time.