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Persist long-term AI memory with semantic retrieval and knowledge graph context.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Memory MCP" yet — see the docs or source repo.
Use Memory MCP to store this long-term memory: the user's name is Li Ming, they prefer concise answers, want Chinese explanations for English terms, and receive project summaries every Monday. Prioritize retrieving these preferences in future conversations.
A summary of stored memory entries and reusable user preference context for future conversations.
Use Memory MCP to retrieve long-term memories related to the 'mobile app redesign' and summarize the previously discussed goals, constraints, key decision-makers, and unresolved issues.
A project background summary built from past memories to quickly restore context.
Use Memory MCP to update the client profile for 'Xinghai Tech': the old record shows a budget of 500,000, while a new message says it has changed to 800,000. Keep both records and label the conflict source and timestamp.
An updated entity memory record with conflict labels, source notes, and timestamps.
Persistent knowledge-graph memory for MCP with semantic search and version tracking.
Give AI chatbots autonomous long-term memory with monitoring and consolidation.
Give AI assistants persistent memory with automatic retrieval and organization.
Give AI clients persistent long-term memory with search and organization.
Give AI agents persistent knowledge-graph memory and cross-session retrieval.
Enable context-aware memory retrieval with authority weighting and conflict detection.