Memory MCP Server

This MCP server provides knowledge graph-based persistent memory functionality designed to enhance AI assistants with reliable, structured information storage and retrieval. Developed by Anthropic in TypeScript, it addresses the critical need for AI systems to maintain contextual awareness across multiple conversations and interactions. By leveraging knowledge graph architecture, the server enables AI assistants to build, update, and access interconnected information repositories that persist beyond individual sessions, significantly improving the quality and consistency of assistant responses.

The Memory server supports comprehensive knowledge management capabilities including entity creation and relationship mapping, semantic query resolution, and intelligent information retrieval. It facilitates dynamic memory updates, conflict resolution for competing information, and contextual relevance ranking to ensure assistants access the most pertinent stored knowledge. The system handles complex relationship structures, enabling assistants to understand nuanced connections between stored entities and make informed decisions based on accumulated historical context.

Compatible with any client supporting the Model Context Protocol, this server integrates seamlessly into diverse AI assistant architectures and applications. Typical use cases include customer support systems requiring consistent interaction history, personal AI assistants building long-term user preference models, research applications needing persistent knowledge accumulation, and multi-turn conversational systems requiring coherent memory management. Organizations deploying sophisticated AI solutions benefit from the server's ability to transform stateless interactions into context-aware, memory-informed conversations.