Flagged: reads sensitive env vars. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by quoroom-ai · MCP Server · ★ 796
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is room safe to install? View the security audit →
Quoroom An open research project in autonomous agent collectives. A single agent thinks. A collective decides. We're building the swarm. Queen, Workers, Quorum. Goals, skills, self-modification, wallet — local-first on your machine, with optional cloud swarm runtime on quoroom.io. Local · Cloud Local/cloud split: Local app + install surface: Cloud app + API + public rooms + swarm instances: <video src="docs/demo.mp4" autoplay lo
| Stars | 796 |
| Forks | 26 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 65.7277012082562/100 |
| Open Issues | 6 |
| Last Updated | 2026-04-12 |
| Created | 2026-02-19 |
| Platforms | claude-code, codex, mcp, node |
| Est. Tokens | ~2067k |
Looking for a room alternative? If you're comparing room with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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room is Open-source earning-focused swarm intelligence engine. Self-governing AI collectives (queen, workers, quorum voting) running locally via MCP. Works with Claude Code, Codex, or pay-per-use APIs.. It is categorized as a MCP Server with 796 GitHub stars.
room is primarily written in TypeScript. It covers topics such as ai, automaton, claude.
You can find installation instructions and usage details in the room GitHub repository at github.com/quoroom-ai/room. The project has 796 stars and 26 forks, indicating an active community.
room is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to room on Agent Skills Hub include toolhive-studio, mcp-client-for-ollama, claude-notifications-go. 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: