agent-memory-persistenceProvide long-term memory persistence for AI agents with SQLite-backed storage, structured metadata, vector embeddings, semantic retrieval, lifecycle manageme...
Install via ClawdBot CLI:
clawdbot install imgolye/agent-memory-persistenceGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Potentially destructive shell commands in tool definitions
exec(Audited Apr 17, 2026 · audit v1.0
Generated Mar 21, 2026
Enables support agents to maintain context across multiple interactions with the same user, recalling past issues and solutions. This reduces repetition and improves resolution times by providing a persistent memory of user history and preferences.
Allows educational AI to track student progress, learning gaps, and preferences over time. It can retrieve past lessons and tailor new content based on stored memories, enhancing personalized learning experiences.
Supports healthcare agents in storing and retrieving patient data, symptoms, and treatment histories across sessions. This aids in continuity of care by enabling semantic search for similar cases and time-based filtering.
Helps shopping bots remember user preferences, past purchases, and browsing history to offer personalized recommendations. It uses vector search to find similar products and filters memories by session for targeted suggestions.
Facilitates internal AI agents in storing and retrieving organizational knowledge, documents, and metadata. Teams can query memories by user or type, with semantic search to find relevant information quickly.
Offer the skill as a cloud-based service with tiered pricing based on memory storage volume and query limits. Revenue comes from monthly subscriptions, targeting businesses needing scalable AI memory without infrastructure management.
Sell licenses for on-premise deployment, allowing enterprises to host the skill internally for data security. Revenue is generated through one-time license fees and optional support contracts, appealing to regulated industries.
Provide a free version with basic memory storage and retrieval, while charging for advanced features like high-volume vector search or custom metadata. Revenue comes from upgrades and enterprise add-ons, attracting developers and small teams.
💬 Integration Tip
Start by integrating the MemoryManager with a simple SQLite path and basic CRUD operations, then gradually add vector embeddings for semantic retrieval as needed.
Scored Apr 19, 2026
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