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 edwin-hao-ai · MCP Server · ★ 216
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Awareness-Local safe to install? View the security audit →
Awareness Local Languages: English | 简体中文 Give your AI agent persistent memory. One co
| Stars | 216 |
| Forks | 3 |
| Language | JavaScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 65.7081445410709/100 |
| Open Issues | 1 |
| Last Updated | 2026-05-04 |
| Created | 2026-03-22 |
| Platforms | browser, claude-code, mcp, node |
| Est. Tokens | ~1174k |
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Awareness-Local is Local-first AI agent memory — one command, works offline, no account needed. Give your Claude Code, Cursor, Windsurf, OpenClaw agent persistent memory. Markdown storage, hybrid search (FTS5 + embeddin. It is categorized as a MCP Server with 216 GitHub stars.
Awareness-Local is primarily written in JavaScript. It covers topics such as ai-agent, ai-memory, claude-code.
You can find installation instructions and usage details in the Awareness-Local GitHub repository at github.com/edwin-hao-ai/Awareness-Local. The project has 216 stars and 3 forks, indicating an active community.
Awareness-Local is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Awareness-Local on Agent Skills Hub include omega-memory, Ori-Mnemos, memorix. 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: