MeiGen-AI-Design-MCP: Discover inspiration and create images and videos with the latest AI models

by jau123 · MCP Server · ★ 1.8k

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

Featured in: Image Generation

How to install MeiGen-AI-Design-MCP

/plugin marketplace add jau123/MeiGen-AI-Design-MCP

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

Security audit verdict: SAFE · quality 77/100

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-image-generationchatgptclaudecodexmcpmcp-serveropenclawseedance

Quick Facts

Stars1,799
Forks236
LanguageTypeScript
CategoryMCP Server
LicenseMIT
Quality Score77/100
Last Updated2026-11-06
Created2026-02-07
Platformsclaude-code, codex, mcp, node
Est. Tokens~17k

About MeiGen-AI-Design-MCP

MeiGen AI Design MCP Turn Claude Code / OpenClaw into your personal design assistant rivaling LovartLocal ComfyUI generation, API integration, 1,300+ pro prompt library, multi-direction parallel output Quick Start &bull; Demo &bull; Features &bull; Providers &bull; Commands <p

Compatible Skills

These tools work well together with MeiGen-AI-Design-MCP for enhanced workflows:

  • nano-banana-pro-prompts-recommend-skill — semantic(0.30)+complementary+same_lang+similar_pop+shared_platform (61%)
  • claude-art-skill — semantic(0.21)+complementary+same_lang+similar_pop+shared_platform (52%)
  • _Book_Claude-Code — semantic(0.19)+complementary+same_lang+similar_pop+shared_platform (52%)
  • prompt-library — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (51%)
  • agentation — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (51%)

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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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