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 lidge-ai · MCP Server · ★ 853
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ima2-gen safe to install? View the security audit →
Generate, branch and clean up images and video on your own machine. One local studio for GPT, Grok, Gemini, NovelAI and ComfyUI. Use it from the browser, the Mac app, the CLI, or hand it to your coding agent. <img src="https://img.shields
| Stars | 853 |
| Forks | 136 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 69.5073792852145/100 |
| Open Issues | 2 |
| Last Updated | 2026-10-03 |
| Created | 2026-04-21 |
| Platforms | gemini, mcp, node |
| Est. Tokens | ~22k |
These tools work well together with ima2-gen for enhanced workflows:
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ima2-gen is Local-first visual generation runtime and studio for people and coding agents, with reproducible image and video workflows across multiple providers.. It is categorized as a MCP Server with 853 GitHub stars.
ima2-gen is primarily written in TypeScript. It covers topics such as ai-agent, gemini, grok.
You can find installation instructions and usage details in the ima2-gen GitHub repository at github.com/lidge-ai/ima2-gen. The project has 853 stars and 136 forks, indicating an active community.
ima2-gen is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ima2-gen on Agent Skills Hub include ima2-gen, comfyui-mcp, py-gpt. 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: