universal-image-mcp: Provider-neutral image generation and editing MCP with a Codex Skill

by Onward0131 · MCP Server · ★ 10

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

Security audit verdict: SAFE · quality 68/100

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.

codexgeminiimage-generationmcpopenai-compatible

Quick Facts

Stars10
Forks0
LanguageJavaScript
CategoryMCP Server
LicenseMIT
Quality Score68/100
Last Updated2026-10-15
Created2026-08-04
Platformscodex, gemini, mcp, node
Est. Tokens~14k

About universal-image-mcp

Provider-neutral image generation and editing MCP with a Codex Skill. Supports OpenAI Images, Gemini, and chat image APIs.

Compatible Skills

These tools work well together with universal-image-mcp for enhanced workflows:

  • ilab-gpt-conjure — semantic(0.47)+complementary+shared_fw(openai)+same_lang+shared_platform (64%)
  • ilab-conjure — semantic(0.47)+complementary+shared_fw(openai)+same_lang+shared_platform (64%)

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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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