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Give AI persistent memory, task context, and semantic search under user control.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "memoryd" yet — see the docs or source repo.
Use memoryd to create a long-term memory layer for my AI assistant: store my project notes, to-dos, and decision logs from the past 30 days, and enable semantic search and topic-based linking.
A persistent memory structure, linked task graph, and semantically searchable contextual results.
Retrieve records related to 'user growth experiments' from memoryd, summarize key decisions, unfinished items, and related contacts, and help me resume interrupted work.
A summary of historical context, an action list, and references to relevant memory entries.
List memory entries in memoryd related to 'product roadmap' sorted by time, and indicate that the data is stored on a user-controlled DWN for later auditing and cleanup.
A time-ordered memory list with clear data ownership, storage location, and manageability details.
Persist long-term AI memory with semantic retrieval and knowledge graph context.
Give AI assistants a persistent, searchable memory layer and context management.
Give AI agents persistent memory and semantic retrieval across conversations.
Lightweight vector memory for AI agents to store, search, and delete memories.
Give MCP clients durable memory for recalling user and project context.
Give AI agents vector memory to reuse past solutions for similar requests.