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Give LLMs persistent memory to store and retrieve information through MCP.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Tiger Memory MCP Server" yet — see the docs or source repo.
Save the following user preferences to memory and prioritize them in future conversations: the user prefers concise answers, wants Chinese responses, and cares about API integration and performance optimization.
The tool stores the user preferences in memory so they can be retrieved and applied later.
Retrieve the previously stored context for the 'Tiger App refactoring project' from memory and summarize the goals, tech stack, and current action items.
It returns the stored project context and summarizes it into a usable working brief.
First read the stored memory about the last meeting notes, then generate today's follow-up plan based on the recorded decisions.
It retrieves prior memory first, then produces a follow-up task plan that continues from the previous discussion.
Persistent knowledge-graph memory for MCP with semantic search and version tracking.
Give AI agents persistent memory and semantic retrieval across conversations.
Provide shared cross-session memory storage, retrieval, and governance for MCP AI tools.
Give AI coding tools persistent memory across sessions, devices, and workflows.
Share memory, preferences, and chat history across AI assistants.
Give AI clients persistent long-term memory with search and organization.