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Give AI assistants persistent memory with vector search, relationships, and access control.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "remember-mcp" yet — see the docs or source repo.
Use remember-mcp to add long-term memory to my AI assistant: store user preferences, past tasks, and key entity relationships, and enable semantic search over relevant records.
Returns a memory structure plan, the types of information to store, and a retrieval approach for querying relevant memories.
Use remember-mcp to design a multi-tenant memory setup so different team members and AI assistants can access project docs, meeting conclusions, and client context by trust level.
Outputs a plan for tenant isolation, permissions, trust-based access control, and how shared team memory should be organized.
Use remember-mcp to organize product requirements, owners, milestones, and risks into a connected memory base for future AI Q&A and context tracking.
Generates a knowledge memory design including entity relationships, storage recommendations, and future retrieval methods.
Enable AI clients to remember user preferences across conversations with vector search.
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 a persistent, searchable memory layer and context management.
Give AI coding assistants persistent, conflict-aware memory across projects and sessions.