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 SFKislev · MCP Server · ★ 76
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Flue safe to install? View the security audit →
-- Flue Let agents control desktop software A tiny bridge that lets your coding agents drive desktop software - Photoshop, Premiere, Blender, Unity, and more - directly from the shell. Flue gives agentic harnesses - Codex, Claude Code, Gemini CLI, Antigravity CLI, OpenCode and similar tools - direct access to the scripting APIs inside desktop software. A single covers many apps across Adobe Creative Cloud, Autodesk, Microsoft Office, and game engines. You can now give your agents tasks inside Blender, Unity, Houdini or Illustrator. Flue is a generalized framework. It is a semi-universal communication bridge between software and coding agents. [It is simpler than MCP servers](https://githu
| Stars | 76 |
| Forks | 5 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 61.4813340713964/100 |
| Last Updated | 2026-09-01 |
| Created | 2026-04-17 |
| Platforms | claude-code, cli, codex, gemini, mcp, python |
| Est. Tokens | ~14k |
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Flue is Let agents control many desktop software directly from the cli, with one pip install, and no MCP servers.. It is categorized as a MCP Server with 76 GitHub stars.
Flue is primarily written in Python. It covers topics such as 3dsmax, adobe, adobe-after-effects.
You can find installation instructions and usage details in the Flue GitHub repository at github.com/SFKislev/Flue. The project has 76 stars and 5 forks, indicating an active community.
Flue is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Flue on Agent Skills Hub include agenttrace, agent-skills, llm-api-setup-guides. 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.
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