$ loading_
Give AI agents persistent knowledge-graph memory and cross-session retrieval.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-memory-server" yet — see the docs or source repo.
Save this to long-term memory: I prefer Chinese replies, concise output, and my project codename is Aurora. In future sessions, prioritize these preferences.
The tool stores the preferences in persistent memory and retrieves them in future sessions.
Remember this: Project Apollo uses PostgreSQL, is deployed in ap-southeast-1, and is owned by Lin. Then tell me the deployment region and owner.
The tool first stores the project facts, then retrieves and returns the requested details.
Create linked memory for 'Client Acme', 'Contact Eva', 'Requirement: SSO', and 'Status: pilot phase', and return the full context when Acme is mentioned later.
The tool stores entities and relationships as structured memory, enabling later context retrieval by name.
Developers building MCP-based AI assistants can use it to store user preferences, project context, and past facts so the assistant remembers across sessions. This reduces repeated explanations and improves continuity.
Research or product teams can store people, projects, and requirements as knowledge-graph memory and let an AI assistant retrieve them by relationship and context. It fits workflows that need continuously accumulated structured background knowledge.
Teams with stronger data-control requirements can self-host this memory server and manage stored memory through its web dashboard. It suits organizations that want AI memory capabilities in their own environment.
It is a self-hosted knowledge-graph memory server for AI agents. Through 7 MCP tools, automatic instructions, and a web dashboard, it gives AI assistants persistent, retrievable memory across sessions.
The provided description explicitly says it is self-hosted, so it can run in your own environment. Detailed deployment steps are not provided here; see the source repository.
The description emphasizes persistent memory, a knowledge graph, and cross-session retrieval, so it is more than just keeping a single chat log. For implementation details and exact retrieval behavior, see the source repository.
Give AI assistants a persistent, searchable memory layer and context management.
Provide shared cross-session memory storage, retrieval, and governance for MCP AI tools.
Give AI agents persistent memory and semantic retrieval across conversations.
Persistent knowledge-graph memory for MCP with semantic search and version tracking.
Automatically stores technical knowledge and retrieves relevant context across future AI sessions.
Give AI assistants persistent memory, entity storage, and semantic search across sessions.