Frequently Asked Questions

Q: What is Memento MCP? A: Memento MCP is a knowledge graph memory system designed for large language models (LLMs), providing them with scalable, high-performance memory capabilities including semantic retrieval, contextual recall, and temporal awareness.

Q: How does Memento MCP enhance LLM capabilities? A: By integrating with LLMs through the Model Context Protocol (MCP), Memento MCP enables LLMs to access and interact with external data sources and tools, enhancing their memory and retrieval capabilities.

Q: What are the core components of Memento MCP? A: The core components include entities, relations, semantic search, temporal awareness, confidence decay, and advanced metadata management.

Q: How does Memento MCP handle data storage? A: Memento MCP uses Neo4j as its storage backend, consolidating both graph and vector storage into a single database, which is optimized for scalability and performance.

Q: Can Memento MCP be integrated with existing AI platforms? A: Yes, Memento MCP can be integrated with platforms like UBOS, enhancing AI agents’ memory capabilities and providing more intelligent and context-aware interactions.