agentmemoGive your AI agent persistent memory and human-in-the-loop approval — across sessions, across models. AgentMemo is a cloud API + MCP server that lets agents...
Install via ClawdBot CLI:
clawdbot install iiamit/agentmemoGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Sends data to undocumented external endpoint (potential exfiltration)
POST → https://api.agentmemo.net/memoriesCalls external URL not in known-safe list
https://agentmemo.netAudited Apr 18, 2026 · audit v1.0
Generated Mar 22, 2026
An AI customer support agent uses AgentMemo to store past interactions with customers, such as previous issues and resolutions. This allows the agent to recall customer history across sessions, providing personalized and efficient support without starting from scratch each time.
An AI project assistant stores project deadlines, task assignments, and meeting notes in AgentMemo. It can search for relevant information when users ask about project status, ensuring consistent memory across different models or sessions, and request approval before sending critical updates to stakeholders.
An AI tutor uses AgentMemo to remember a student's learning progress, strengths, and weaknesses. It retrieves past lessons and preferences to tailor new content, and requests human approval before recommending advanced or sensitive topics, enhancing personalized education over time.
An AI scheduler stores patient preferences, appointment histories, and medical notes in AgentMemo. It recalls past interactions to suggest suitable appointment times and requests approval before booking sensitive procedures, ensuring compliance and patient privacy across healthcare sessions.
An AI shopping assistant uses AgentMemo to remember user preferences, past purchases, and browsing history. It provides personalized product recommendations and requests approval before processing large orders or sharing data with third parties, improving cross-session shopping experiences.
Offer a free tier with limited memories and searches to attract individual developers and small teams, then charge for higher limits, advanced features like priority approval queues, and enterprise support. Revenue comes from subscription tiers and custom integrations.
Monetize the AgentMemo API by charging based on usage metrics such as number of memories stored, searches performed, and approval requests. Target AI developers and companies building agent-based applications, with pricing tiers scaled to volume and support levels.
Sell enterprise licenses to large organizations needing persistent memory and approval workflows for internal AI agents. Include features like on-premise deployment options, enhanced security, and dedicated support, with revenue from annual contracts and customization services.
💬 Integration Tip
Start by setting up the free API key and testing with basic memory storage and recall in a development environment before scaling to production workflows.
Scored Jun 19, 2026
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