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Give AI agents local-first memory, retrieval, and spaced learning workflows.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "MnemoQ" yet — see the docs or source repo.
Please save the following project learning into MnemoQ and link it by topic: In our customer support bot launched in May, adding an intent clarification step improved task completion by 18%, but increased first response time by 0.7 seconds.
The tool creates a structured memory entry with key facts, topic links, and records for later retrieval.
Retrieve MnemoQ records related to 'RAG retrieval ranking optimization' and summarize, in chronological order, the methods we tried, their results, and why they failed.
Outputs a timeline-based summary from memory, helping you review prior approaches and lessons learned quickly.
Please review technical learning records added to MnemoQ in the past two weeks and generate a spaced repetition review list based on forgetting risk and importance, prioritizing what should be reviewed today.
Returns a prioritized review task list to help the agent or user reinforce important knowledge.
Gives AI coding agents persistent local memory across sessions for decisions and rules.
Provide local-first, auditable, consent-gated memory across AI tools via MCP.
Give AI agents persistent semantic memory with search, decay, and deduplication.
Give AI persistent, synced memory with full-text and semantic hybrid search.
Give AI agents persistent memory and hosted access for continuity across sessions.
Give coding agents auditable local-first long-term memory for better continuity.