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 xiayu1987 · MCP Server · ★ 146
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is noobot safe to install? View the security audit →
Noobot 中文 | English Noobot is a full-stack AI chat system built with Node.js + Vue. Features Multi-user isolated workspace/session Agent tools + skill extension SSE streaming output + WebSocket long connection Agent proxy gateway for resilient WebSocket fanout/replay One-command deployment via (PM2 + Caddy) Connector support (database/terminal/email) MCP server integration Multi-model provider management with scenario-based routing Project Structure Quick Start bash git clone https://github.com/xiayu1987/noobot.git cd n
| Stars | 146 |
| Forks | 12 |
| Language | JavaScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 70.9587501786361/100 |
| Open Issues | 2 |
| Last Updated | 2026-09-10 |
| Created | 2026-04-17 |
| Platforms | browser, mcp, node |
| Est. Tokens | ~14k |
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noobot is Cheapest Money-Saving Self-hosted AI agent workspace with tool calling, MCP, multi-model routing, sandboxed execution, multi-agent workflows, and LLM-authored 3D character animation rendered with Thre. It is categorized as a MCP Server with 146 GitHub stars.
noobot is primarily written in JavaScript. It covers topics such as 3d, ai-agent, ai3d.
You can find installation instructions and usage details in the noobot GitHub repository at github.com/xiayu1987/noobot. The project has 146 stars and 12 forks, indicating an active community.
noobot is released under the MIT license, making it free to use and modify according to the license terms.
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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: