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Give AI agents decaying memory storage, retrieval, and permanent journal verification.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "memory-decay" yet — see the docs or source repo.
Integrate memory-decay into my AI assistant: let short-term preferences and context decay over time, keep recently accessed information longer, and write key decisions to the permanent journal. Provide example flows for memory write, read, and verification.
A setup plan showing how to manage decaying memory, preserve important records, and handle typical calls.
I want the agent to revisit past memories about user requirements, but only trust content that can be verified in the permanent journal. Design a retrieval strategy: read related memories first, then check the journal, and finally rank results by confidence.
A retrieval strategy with verification steps to distinguish faded memories from verifiable facts.
Use memory-decay to design memory rules for a long-running research agent: let temporary clues decay automatically, extend retention for repeatedly used knowledge, write milestone conclusions to the permanent journal, and explain suitable parameters and maintenance tips.
A memory strategy for long-running tasks, including decay rules, retention conditions, and permanent logging advice.
Give AI assistants persistent memory, adaptive recall, and graph-based knowledge retrieval.
Give AI agents persistent memory and semantic retrieval across conversations.
Give AI agents persistent brain-inspired memory with reflection and replay.
Give AI agents persistent semantic memory with search, decay, and deduplication.
Persistent knowledge-graph memory for MCP with semantic search and version tracking.
Enable AI assistants to store, search, and manage persistent semantic memories.