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 53AI · MCP Server · ★ 4.7k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is 53AIHub safe to install? View the security audit →
Cloud Service · Local Deployment · Documentation · Demo Site 53AI Hub is an open-source AI portal, which enables you to quickly build a operational-level AI portal to launch and operate AI agents, prompts, and AI tools. It supports seamless integration with development platforms like Coze, Dify, FastGPT, RAGFlow, and 53AI Studio, and cloud platforms such as Aliyun , Tencent Cloud , and Baidu Cloud, helping developers and enterprises build production-grade AI portals without complex integrations. Even users with no technical background can participate easily, significantly lowering the barrier to AI inplementation. Key features are as follows: 1. Platform Integration: Supports integration with mainstream agent development pl
| Stars | 4,658 |
| Forks | 516 |
| Language | Go |
| Category | MCP Server |
| Quality Score | 67.6213294221524/100 |
| Open Issues | 21 |
| Last Updated | 2026-09-22 |
| Created | 2025-04-24 |
| Platforms | go, mcp |
| Est. Tokens | ~16k |
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53AIHub is 53AI Hub is an open-source AI portal and knowledge base for managing enterprise knowledge, AI agents, prompts, and AI tools, seamlessly integrating with Coze, Dify, FastGPT, RAGFlow. 一个AI知识库与Agent门户. It is categorized as a MCP Server with 4.7k GitHub stars.
53AIHub is primarily written in Go. It covers topics such as coze, dify, fastgpt.
You can find installation instructions and usage details in the 53AIHub GitHub repository at github.com/53AI/53AIHub. The project has 4.7k stars and 516 forks, indicating an active community.
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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: