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Extract and manage user memory for consistent personalization across LLMs.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Samantha" yet — see the docs or source repo.
Extract the user’s long-term preferences, preferred tone, and important background from the following multi-turn conversation, and organize them into updatable memory entries. Separate facts, preferences, and unverified information.
A structured user memory list that the assistant can reuse for personalized future conversations.
Summarize this user’s past conversations from Model A into shared memory for Model B to use. Deduplicate entries, merge similar items, and label each memory with its source and confidence level.
A unified cross-model memory store that preserves a consistent user experience after switching models.
Review the existing user memory, identify outdated, conflicting, or low-confidence information, and suggest what to keep, update, or remove. Then generate a cleaned and current memory version.
A cleaned, up-to-date user memory set along with maintenance recommendations.
Run commands, manage long jobs, and transfer files in AI sandboxes.
Give AI agents persistent memory and semantic retrieval across conversations.
Provide shared cross-session memory storage, retrieval, and governance for MCP AI tools.
Enable MCP clients to remember users across chats with vector search.
Manage personal memory, profiles, notes, and semantic search in one place.
Persistent knowledge-graph memory for MCP with semantic search and version tracking.