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Search and write unified memory across files, vectors, and temporal knowledge graphs.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "universal-memory-service" yet — see the docs or source repo.
Write the following user preferences into universal-memory-service and suggest searchable keywords: The user prefers Simplified Chinese and is interested in cloud computing, open-source databases, and infrastructure automation.
Returns the write result plus keywords or index hints for future memory retrieval.
Use universal-memory-service to retrieve historical memory related to “vector database selection” and summarize file records, semantically similar vector entries, and linked facts from the knowledge graph.
Provides a consolidated summary of retrieved results with matched content grouped by source.
Store the following research progress in universal-memory-service and create time-based knowledge links: data collection finished in March, cleaning in April, model training started in May, and a recall drop was found in June.
Returns a write confirmation showing event order over time and the knowledge relationships between them.
Persist long-term AI memory with semantic retrieval and knowledge graph context.
Provide self-hosted, Git-backed shared memory for multi-agent search and updates.
Store and search memories across OpenMemory and Cipher through one unified MCP.
Provide shared cross-session memory storage, retrieval, and governance for MCP AI tools.
Give AI agents vector memory to reuse past solutions for similar requests.
Provide persistent shared memory, entity extraction, and hybrid search for AI tools.