by Atmosphere · MCP Server · ★ 3.8k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
brew install Atmosphere/tap/atmosphere
npm install atmosphere.jsTaken from the project's README on GitHub. Check the security audit before running it.
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.
| Stars | 3,830 |
| Forks | 763 |
| Language | Java |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 65/100 |
| Open Issues | 9 |
| Last Updated | 2026-11-04 |
| Created | 2010-06-30 |
| Platforms | java, mcp |
| Est. Tokens | ~23k |
Atmosphere The real-time engine for AI agents on the JVM. Tokens flow from the LLM runtime to the client through a broadcaster you can filter, gate, and observe — over WebSocket, SSE, long-polling, or gRPC, and out through MCP, A2A, and AG-UI. A plain @Agent is a full deep agent, batteries-included, and Atmosphere handles reconnect, authorization, and governance.
These tools work well together with atmosphere for enhanced workflows:
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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: