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 weam-ai · MCP Server · ★ 220
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is weam safe to install? View the security audit →
LLMs, Agents, AI Apps, and Team—In One Place, Ready to Use and Expand Website • Docs • Discord -- What is Weam AI Weam is an open source platform that helps teams adopt AI systematically. It includes a complete, production-ready stack with Next.js frontend and Node.js backend - ready to deploy and use immediately. System Requirements: CPU with 4+ core
| Stars | 220 |
| Forks | 91 |
| Language | TypeScript |
| Category | MCP Server |
| Quality Score | 65.514037602824/100 |
| Open Issues | 22 |
| Last Updated | 2026-07-28 |
| Created | 2025-06-27 |
| Platforms | browser, claude-code, mcp, node |
| Est. Tokens | ~16k |
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weam is Web app for teams of 20+ members. In-built connections to major LLMs via API. Share chats, prompts, and agents in team or private folders. Modern, fully responsive stack (Next.js, Node.js). Deploy you. It is categorized as a MCP Server with 220 GitHub stars.
weam is primarily written in TypeScript. It covers topics such as agent-library, agents, ai.
You can find installation instructions and usage details in the weam GitHub repository at github.com/weam-ai/weam. The project has 220 stars and 91 forks, indicating an active community.
The top alternatives to weam on Agent Skills Hub include c4-genai-suite, flock, minima. 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: