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 Anil-matcha · Agent Tool · ★ 50
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is MiniMax-H3-API safe to install? View the security audit →
MiniMax H3 API: Python SDK for AI Video Generation Python SDK for the MiniMax H3 API on Muapi. Generate video from text, animate a still image, or create a controlled transition between first and last frames with one API key. ▶ Watch: How to Access MiniMax Hailuo H3 API (Step-by-Step Guide): Native 2K Video Generation with Sound Related Projects Open-Generative-AI — open-source studio and model hub for generative image and video workflows. awesome-ai-video-models — compare leading AI video models, API access, and pricing. Seedance-2-API — Python SDK for ByteDance Seedance text-to-video and image-to-video workflows. [Veo-4-API](https://githu
| Stars | 50 |
| Forks | 12 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 75.7740665645412/100 |
| Last Updated | 2026-10-01 |
| Created | 2025-12-08 |
| Platforms | python |
| Est. Tokens | ~3k |
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MiniMax-H3-API is Python SDK for the MiniMax H3 API — text-to-video, image-to-video, and first/last-frame video generation via Muapi.. It is categorized as a Agent Tool with 50 GitHub stars.
MiniMax-H3-API is primarily written in Python. It covers topics such as ai-tools, ai-video, api.
You can find installation instructions and usage details in the MiniMax-H3-API GitHub repository at github.com/Anil-matcha/MiniMax-H3-API. The project has 50 stars and 12 forks, indicating an active community.
MiniMax-H3-API is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to MiniMax-H3-API on Agent Skills Hub include awesome-seedance-2.5-prompts-skills, Sora-FullStack, vibeframe. 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: