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Provide isolated namespaces and persistent memory across multi-user AI sessions.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "xmszm-memory" yet — see the docs or source repo.
Use xmszm-memory to create an isolated namespace for the product team, save our product goals, core terminology, and recent decisions, and prioritize this memory in future conversations.
An isolated team memory space is created, with key information persistently stored for future sessions.
Using xmszm-memory, save preferences, task history, and preferred formats for different users separately, ensuring their memories never mix.
Separate memory records are maintained for each user, preventing cross-user context contamination.
Read the project background, action items, and unresolved questions saved in the previous session from xmszm-memory, then continue assisting me based on them.
Historical memory is restored from persistent storage so the assistant can continue work seamlessly in a new session.
Store and query namespaced key-value memory for persistent agent context.
Give AI agents persistent memory and semantic retrieval across conversations.
Provide shared cross-session memory storage, retrieval, and governance for MCP AI tools.
Persistent knowledge-graph memory for MCP with semantic search and version tracking.
Provide slim memory for AI assistants while reducing context token usage.
Persist conversational memory with SQLite and retrieve context using metadata.