$ loading_
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 local AI CLI tools persistent cross-session memory with private context retention.
Give AI agents vector memory to reuse past solutions for similar requests.