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by henrychong-ai • Uncategorized
A scalable, high-performance knowledge graph memory system with semantic retrieval, contextual recall, and temporal awareness for MCP-compatible LLM clients.
Resilient and persistent long-term memory with ontological knowledge.
Semantic search capabilities combining vector embeddings and keyword search.
Temporal awareness and version history of knowledge graph data.
This MCP server provides a resilient, adaptive, and persistent long-term ontological memory by leveraging Neo4j as a unified storage backend for graph and vector data. It supports advanced features such as semantic search with vector embeddings, temporal versioning of entities and relations, confidence decay over time, rich metadata, and optimized batch operations for high performance. The system integrates seamlessly with MCP clients like Claude Desktop, enabling enhanced contextual understanding and memory capabilities for large language models.