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Persistent knowledge-graph memory for MCP with semantic search and version tracking.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-memory-server" yet — see the docs or source repo.
Please write the following to memory: entity “Client A”, attribute “prefers weekly reports in PDF”, observation “requested more chart summaries last week”, and link it to entity “Project North Star.”
Returns saved entities, observations, and relations for future conversations to reuse.
Search memory for items most relevant to “client feedback on report visualization,” rank by semantic similarity, and output related entities, timeline, and relation summaries.
Returns the most relevant past records to quickly restore context for the model.
Show the last three updates for entity “Project North Star,” including new observations, relation changes, and timestamps for each revision.
Outputs the entity’s version history for auditing and tracking information changes.
Give AI agents persistent memory and semantic retrieval across conversations.
Give LLMs persistent semantic memory and vector search for better context continuity.
Give AI assistants persistent memory with vector search, relationships, and access control.
Enable AI clients to remember user preferences across conversations with vector search.
Lightweight vector memory for AI agents to store, search, and delete memories.
Give AI knowledge-graph memory with cloud persistence and semantic search.