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 ourmem · MCP Server · ★ 199
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is omem safe to install? View the security audit →
OMEM Shared Memory That Never Forgets English | 简体中文 The Problem Your AI agents have amnesia — and they work alone. 🧠 Amnesia — every session starts from zero. Preferences, decisions, context — all gone. 🏝️ Silos — your Coder agent can't access what your Writer agent learned. 📁 Local lock-in — memory tied to one machine. Switch devices, lose everything. 🚫 No sharing — team agents can't share what they know. Every agent re-discovers the same things. 🔍 Dumb recall — keyword match only. No semantic understanding, no relevance ranking. 🧩 No collective intelligence — even when agents work on the same team, there's no shared knowledge layer. ourmem fixes all of this. What is ourmem ourmem gives AI agents shared persistent memory — across sessions, devices, agents, and teams. One API key reconnects everything. 🌐 Website: ourmem.ai <td width="50%" va
| Stars | 199 |
| Forks | 9 |
| Language | Rust |
| Category | MCP Server |
| Quality Score | 65.2116580997002/100 |
| Open Issues | 5 |
| Last Updated | 2026-05-24 |
| Created | 2026-03-27 |
| Platforms | claude-code, mcp, rust |
| Est. Tokens | ~116k |
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omem is Shared Memory That Never Forgets — persistent memory for AI agents with Space-based sharing across agents and teams. Plugins for OpenCode, Claude Code, OpenClaw, MCP Server.. It is categorized as a MCP Server with 199 GitHub stars.
omem is primarily written in Rust. It covers topics such as ai-agent, ai-memory, claude-code.
You can find installation instructions and usage details in the omem GitHub repository at github.com/ourmem/omem. The project has 199 stars and 9 forks, indicating an active community.
The top alternatives to omem on Agent Skills Hub include Ori-Mnemos, omega-memory, roampal-core. 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: