atmosphere — security grade SAFE, quality 65/100

Security audit verdict: SAFE · quality 65/100

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 Atmosphere · MCP Server · ★ 3.8k

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

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About atmosphere

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. <img src="https://github.com/Atmosphere/atmosphere/actions/workflows/ci-js.yml/badge.svg?branch=main" alt="CI:

a2aacpagentic-aiai-agentsanthropiccrewaiembabelevent-drivenjavakoog

Quick Facts

Stars3,813
Forks762
LanguageJava
CategoryMCP Server
LicenseApache-2.0
Quality Score65.1101511348012/100
Open Issues7
Last Updated2026-09-18
Created2010-06-30
Platformsbrowser, java, mcp
Est. Tokens~23k

Compatible Skills

These tools work well together with atmosphere for enhanced workflows:

  • JavaClaw — semantic(0.45)+complementary+shared_fw(anthropic,spring)+same_lang+similar_pop+shared_platform (82%)
  • JavaClaw — semantic(0.45)+complementary+shared_fw(anthropic,spring)+same_lang+similar_pop+shared_platform (82%)
  • mateclaw — semantic(0.36)+shared_fw(anthropic,spring)+rare_topics+same_lang+similar_pop+shared_platform (77%)
  • mateclaw — semantic(0.36)+shared_fw(anthropic,spring)+rare_topics+same_lang+similar_pop+shared_platform (77%)
  • spring-ai-agent-utils — semantic(0.38)+complementary+shared_fw(spring)+rare_topics+same_lang+similar_pop+shared_platform (76%)

atmosphere alternative? Top 6 similar tools

Looking for a atmosphere alternative? If you're comparing atmosphere 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.

  • solace-agent-mesh by SolaceLabs · ⭐ 4.9k

    An event-driven framework designed to build and orchestrate multi-agent AI systems. It enables seamless integr

  • voltagent by VoltAgent · ⭐ 10.4k

    AI Agent Engineering Platform built on an Open Source TypeScript AI Agent Framework

  • yu-ai-agent by liyupi · ⭐ 2.7k

    编程导航 2025 年 AI 开发实战新项目,基于 Spring Boot 3 + Java 21 + Spring AI 构建 AI 恋爱大师应用和 ReAct 模式自主规划智能体YuManus,覆盖 AI 大模型接入

  • mcp-memory-service by doobidoo · ⭐ 2.0k

    Open-source persistent memory for AI agent pipelines (LangGraph, CrewAI, AutoGen) and Claude. REST API + knowl

  • trpc-agent-go by trpc-group · ⭐ 1.8k

    A Go framework for building production agent systems with graph workflows, tools, memory, A2A, AG-UI, MCP, eva

  • argo by xark-argo · ⭐ 814

    ARGO is an open-source AI Agent platform that brings Local Manus to your desktop. With one-click model downloa

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Frequently Asked Questions

What is atmosphere?

atmosphere is Portable AI agent runtime for the JVM. One @Agent class runs on Spring AI, LangChain4j, Anthropic, or 9 more behind one SPI. Token streaming, tool calls, human approvals, and governance over WebSocket. It is categorized as a MCP Server with 3.8k GitHub stars.

What programming language is atmosphere written in?

atmosphere is primarily written in Java. It covers topics such as a2a, acp, agentic-ai.

How do I install or use atmosphere?

You can find installation instructions and usage details in the atmosphere GitHub repository at github.com/Atmosphere/atmosphere. The project has 3.8k stars and 762 forks, indicating an active community.

What license does atmosphere use?

atmosphere is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to atmosphere?

The top alternatives to atmosphere on Agent Skills Hub include solace-agent-mesh, voltagent, yu-ai-agent. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

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:

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