genex-desktop: Desktop app for game dev with AI: make games in Unreal Engine, Unity, Godot or the browser

by genex-games · MCP Server · ★ 792

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install genex-desktop

git clone https://github.com/genex-games/genex-desktop.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 63/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

ai-agentsclaude-codecodexgamedevgodotlocal-llmmcpollamarobloxunity

Quick Facts

Stars792
Forks97
LanguageTypeScript
CategoryMCP Server
LicenseMIT
Quality Score63/100
Open Issues59
Last Updated2026-11-04
Created2026-10-02
Platformsbrowser, claude-code, codex, mcp, node
Est. Tokens~15k

About genex-desktop

Desktop app for game dev with AI: make games in Unreal Engine, Unity, Godot or the browser.The agent sets up the engine, builds your game and play-tests it by itself. Download , or from the [latest rel

Compatible Skills

These tools work well together with genex-desktop for enhanced workflows:

  • FreeUltraCode — semantic(0.46)+complementary+same_lang+similar_pop+shared_platform (66%)
  • UltraGameStudio — semantic(0.46)+complementary+same_lang+similar_pop+shared_platform (66%)
  • everything-game-dev-code — semantic(0.52)+complementary+similar_pop+shared_platform (58%)
  • Claw3D — semantic(0.21)+complementary+same_lang+similar_pop+shared_platform (57%)
  • soft-ue-cli — semantic(0.48)+complementary+similar_pop+shared_platform (57%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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