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 claude-world · MCP Server · ★ 70
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🔒 Is claude-world-studio safe to install? View the security audit →
Claude World Studio AI-powered content pipeline: from trend discovery to social publishing. Built with Claude Agent SDK + MCP (Model Context Protocol), featuring 3 integrated MCP servers for real-time trends, web scraping, and research automation. Features One-Stop Pipeline Three clear entry points — no complex menus, just pick and go: Live Agent Execution Watch Claude work in real-time — tool calls shown as collapsible blocks with MCP server badges: trend-pulse (green) — 20 real-time trend sources, zero auth cf-browser (blue) — Cloudflare Browser Rendering for JS pages notebooklm (purple) — Research + artifact generation (podcast/slides/video) studio — Built-in publishing +
| Stars | 70 |
| Forks | 10 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 69.4947285752662/100 |
| Open Issues | 19 |
| Last Updated | 2026-07-09 |
| Created | 2026-03-15 |
| Platforms | claude-code, mcp, node |
| Est. Tokens | ~17k |
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claude-world-studio is AI-powered content pipeline: trend discovery → research → social publishing. Built with Claude Agent SDK + MCP.. It is categorized as a MCP Server with 70 GitHub stars.
claude-world-studio is primarily written in TypeScript. It covers topics such as ai-agent, claude, claude-code.
You can find installation instructions and usage details in the claude-world-studio GitHub repository at github.com/claude-world/claude-world-studio. The project has 70 stars and 10 forks, indicating an active community.
claude-world-studio is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to claude-world-studio on Agent Skills Hub include socialclaw, social-media-caption-generator-claude, UnityMCP. 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: