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 langgenius · MCP Server · ★ 156.9k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is dify safe to install? View the security audit →
Dify Cloud · Self-hosting · Documentation · Dify edition overview <img src="https://cu
| Stars | 156,898 |
| Forks | 24,734 |
| Language | TypeScript |
| Category | MCP Server |
| Quality Score | 62.5975628974575/100 |
| Open Issues | 1093 |
| Last Updated | 2026-09-23 |
| Created | 2023-04-12 |
| Platforms | claude-code, mcp, node |
| Est. Tokens | ~17k |
These tools work well together with dify for enhanced workflows:
Looking for a dify alternative? If you're comparing dify with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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dify is Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without reb. It is categorized as a MCP Server with 156.9k GitHub stars.
dify is primarily written in TypeScript. It covers topics such as agent, agentic-ai, agentic-framework.
You can find installation instructions and usage details in the dify GitHub repository at github.com/langgenius/dify. The project has 156.9k stars and 24734 forks, indicating an active community.
The top alternatives to dify on Agent Skills Hub include ragflow, lobehub, chatgpt-on-wechat. 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: