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Give AI agents persistent memory and semantic retrieval across conversations.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "memdata-mcp" yet — see the docs or source repo.
Save these key meeting decisions to memdata: API version frozen at v2, target release date is August 15, owner is Lina; add tags for future retrieval: release, API, decision.
The tool returns a saved memory record, tags, or a unique ID for later lookup.
Retrieve the historical notes in memdata most relevant to “pricing adjustment plan” and “enterprise customer feedback,” rank them by semantic relevance, and summarize the top five points.
Returns relevant past records and a summary to quickly restore previously discussed context.
Write these user preferences into memdata: prefers concise answers, default output in Chinese, and Python examples first for code; retrieve and apply these preferences before future replies.
After saving the preferences, future conversations can automatically read them and produce more consistent replies.
Give AI agents persistent knowledge-graph memory and cross-session retrieval.
Provide shared cross-session memory storage, retrieval, and governance for MCP AI tools.
Enable MCP clients to remember users across chats with vector search.
Automatically stores technical knowledge and retrieves relevant context across future AI sessions.
Provide persistent local semantic memory for MCP tools to store and search notes.
Persistent knowledge-graph memory for MCP with semantic search and version tracking.