展示HN：QCCBot – 在浏览器标签页中的安卓，带有AI代理控制
八个月前，我看到一个朋友为他的跨境电商业务管理三面墙的手机——充电、切换IP、不断担心被封禁。我问自己：人们到底是想要这些设备，还是只是想要里面的安卓环境？
为了解答这个问题，我们开发了QCCBot。它在ARM服务器上运行完整的安卓实例，并通过浏览器进行流媒体传输。打开一个标签页，你就能获得一部手机。无需硬件、无需电缆，也不必为100台机器轮流充电。
现在我们有了真实的用户——跨境电商、TikTok运营、应用测试、远程工作。老实说，我们的用户在发现使用场景方面比我们更早。
我们接下来要构建的目标是：
能够不仅仅查看安卓环境的AI代理——它们能够在其中操作。打开应用、执行任务、监控状态、反馈结果。常规操作不再需要人工干预。
我们刚刚发布的基础设施部分包括：
• 任务执行API（OpenAPI）
• 脚本模板商店（约30个模板，选择行为并部署）
• 私有部署中的AgentV2
• 通过OpenClaw集成的基于ADB的代理控制
当前的真实限制：
• 流媒体延迟仍在改进中
• 指纹模拟并不完美
• 完全自主操作仍在构建中
• 当我们重新设计用户界面时，遭到了高级用户的批评（这很公平）
我们收集的挫折比功能还要多。现在还很早。但真实用户每天都在告诉我们哪些地方不好——这比赞美更有价值。
试试吧：qccbot.com
我很乐意深入探讨ARM虚拟化方法、代理控制层或流媒体架构。同时也真心希望了解是否有其他构建AI代理的人遇到过“需要持久的移动环境”的问题。
查看原文
Eight months ago I watched a friend manage three walls of phones for his cross-border e-commerce operation — charging, swapping IPs, constantly worrying about bans.
I asked myself: do people actually want the boxes, or just the Android environment inside?
We built QCCBot to answer that. Full Android instances running on ARM servers, streamed to a browser. Open a tab, you get a phone. No hardware, no cables, no charging 100 machines on rotation.
We have real users now — cross-border e-commerce, TikTok ops, app testing, remote work. Honestly, our users found the use cases before we did.
What we're building toward next:
AI agents that don't just view the Android environment — they operate inside it. Open apps, execute tasks, monitor state, report back. No human in the loop for routine operations.
The infrastructure piece we just shipped:
• Task execution API (OpenAPI)
• Script template store (~30 templates, pick a behavior and deploy it)
• AgentV2 running in private deployment
• ADB-based agent control via OpenClaw integration
Current honest limitations:
• Streaming latency is still a work in progress
• Fingerprint simulation isn't perfect
• Full autonomous operation is still being built out
• We got roasted by power users when we redesigned the UI (fair)
We've collected more scars than features. Still early. But real users are telling us what sucks every day — that's worth more than praise.
Try it: qccbot.com
Happy to go deep on the ARM virtualization approach, the agent control layer, or the streaming architecture. Also genuinely interested in whether anyone building AI agents has hit the "need a persistent mobile environment" problem.