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Give AI agents privacy-first memory storage with fine-grained access control.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "reflect-memory" yet — see the docs or source repo.
Use reflect-memory to store these user memories: prefers concise answers, defaults to Chinese, cares about data privacy; allow only the current AI vendor to read them.
A persistent set of user preference memories is created with fine-grained read permissions.
Read the user’s authorized past memories from reflect-memory and summarize them into a response strategy for more personalized answers.
A summary of authorized memories is returned to guide reply style and content focus.
Create a project memory in reflect-memory: 'The Q3 roadmap is not public yet,' and restrict access to internal models only, blocking external vendors.
A restricted project memory is created with explicit rules for which models or vendors may access it.
Manage persistent agent memories across global or repository-specific scopes.
Share memory, preferences, and chat history across AI assistants.
Provide shared cross-session memory storage, retrieval, and governance for MCP AI tools.
Give AI agents persistent memory and semantic retrieval across conversations.
Give AI coding tools persistent memory across sessions, devices, and workflows.
Enable AI assistants to store, search, and manage persistent semantic memories.