Memory FAQs

Question 1

What is Memory MCP Server?

Accepted Answer

Memory is an enhanced Model Context Protocol (MCP) server that provides persistent knowledge graph memory for AI applications, particularly designed to augment AI models like Claude with long-term recall and organized context across conversations.

Question 2

What advanced features does Memory offer?

Accepted Answer

It includes automatic timestamps for entities and relations, a flexible tags system, importance levels (0-10) for prioritization, advanced filtering combining multiple criteria, and multi-format export options (JSON, CSV, GraphML) for visualization and analysis.

Question 3

How does Memory improve AI interactions?

Accepted Answer

By providing a structured, persistent knowledge graph, Memory enables AI to remember critical information across conversations, ensuring better context, consistent responses, and deeper understanding over time, ultimately leading to more intelligent and personalized interactions.

Question 4

What kind of data structure does Memory use?

Accepted Answer

Memory utilizes an Entity-Relation-Observation (ERO) knowledge graph model, allowing for the storage of distinct entities (nodes), their directed relationships (edges), and specific facts or observations associated with them.

Question 5

Can I integrate Memory with existing graph visualization tools?

Accepted Answer

Yes, Memory supports exporting your knowledge graph data in GraphML format, which is compatible with popular visualization and analysis tools such as Gephi, Cytoscape, and yEd, facilitating easy exploration and understanding of your stored context.

Memory

Memory

Key Features

Use Cases

Key Features

Use Cases