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Give AI clients persistent long-term memory with search and organization.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Memory MCP Server" yet — see the docs or source repo.
Save the following into long-term memory, categorize it under 'user preferences/communication style', and set priority to high: the user prefers concise answers, Chinese by default, and a project summary every Monday.
Returns a memory save result with category, priority, and a summary for future retrieval.
Search long-term memory for items related to 'pricing strategy changes', rank them by semantic relevance, and summarize key past conclusions and open questions.
Outputs relevant memory entries and a decision summary compiled from historical context.
The current memory storage uses local JSON. Explain how to switch to PostgreSQL and list the effects on persistence, scalability, and team sharing after migration.
Provides migration steps, configuration notes, and a comparison between local and cloud storage.
Lightweight vector memory for AI agents to store, search, and delete memories.
Store and retrieve long-term AI memories with semantic search and tags.
Provide long-term memory storage and fast semantic retrieval for AI applications.
Persistent knowledge-graph memory for MCP with semantic search and version tracking.
Give AI agents persistent memory and semantic retrieval across conversations.
Enable AI clients to remember user preferences across conversations with vector search.