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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Review the existing user memory, identify outdated, conflicting, or low-confidence information, and suggest what to keep, update, or remove.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.
Develop and manage SA-MP servers with scripting, plugins, and diagnostics.
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.
Manage personal memory, profiles, notes, and semantic search in one place.
Persistent knowledge-graph memory for MCP with semantic search and version tracking.