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 AmoyLab · MCP Server · ★ 2.2k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Unla safe to install? View the security audit →
Unla - MCP Gateway 🚀 Instantly transform your existing MCP Servers and APIs into MCP endpoints — without changing a line of code. ⚡ Note: Unla is under rapid development! We strive to maintain backward compatibility, but it cannot be 100% guaranteed. Please make sure to check version changes carefully when
| Stars | 2,214 |
| Forks | 180 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 65.634779104944/100 |
| Open Issues | 92 |
| Last Updated | 2026-08-27 |
| Created | 2025-04-15 |
| Platforms | docker, mcp, node |
| Est. Tokens | ~15k |
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Unla is 🧩 MCP Gateway - A lightweight gateway service that instantly transforms existing MCP Servers and APIs into MCP servers with zero code changes. Features Docker deployment and management UI, requiring . It is categorized as a MCP Server with 2.2k GitHub stars.
Unla is primarily written in TypeScript. It covers topics such as awesome, mcp, mcp-adapter.
You can find installation instructions and usage details in the Unla GitHub repository at github.com/AmoyLab/Unla. The project has 2.2k stars and 180 forks, indicating an active community.
Unla is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Unla on Agent Skills Hub include mcp-use, archestra, metamcp. 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: