No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by NevaMind-AI · MCP Server · ★ 14.4k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is memU safe to install? View the security audit →
memU 24/7 Always-On Proactive Memory for AI Agents English Français memU is a memory framework built for 24/7 proactive agents. It is designed for long-running use and greatly reduces the LLM token cost of keeping agents always online, making always-on, evolving agents practical in production systems. memU continuously captures and understands user intent. Even without a command, the agent can tell what you are about to do and
| Stars | 14,420 |
| Forks | 1,071 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 55.6348819576825/100 |
| Open Issues | 122 |
| Last Updated | 2026-09-21 |
| Created | 2025-07-29 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~19k |
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memU is Personal memory across agents. It is categorized as a MCP Server with 14.4k GitHub stars.
memU is primarily written in Python. It covers topics such as agent-memory, claude-skills, harness.
You can find installation instructions and usage details in the memU GitHub repository at github.com/NevaMind-AI/memU. The project has 14.4k stars and 1071 forks, indicating an active community.
The top alternatives to memU on Agent Skills Hub include EverMemOS, chatgpt-on-wechat, claude-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: