FrameHarbor 是一个环境、始终在线的可视化日志，专注于软件质量的工作流程。传统质量保证工具只在故障时刻截取一张截图，而 FrameHarbor 则不断从你的桌面或设备视口编织出一幅滚动的画面画卷，然后通过模型上下文协议（MCP）向 AI 助手展示这幅画卷。可以把它想象成你屏幕的灯塔守护者：它永不休眠，记住每一波浪的形状，当风暴来临时，证据光束已经在等待。

FrameHarbor为将质量保证视为观察科学而非被动任务的团队打造，将被动的屏幕时间转化为结构化、可搜索且丰富的上下文文物。每一帧都是面包屑;每一次会话都是一条线索;每一次调查都是你可以与AI协作者逐帧重玩的故事。

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🌅 FrameHarbor背后的理念

大多数可观测堆栈是为服务器设计的，而不是为前端行为中混乱、人为驱动的像素驱动世界设计。

🎞️ FrameHarbor — Temporal Evidence Vault for AI Quality Assurance

FrameHarbor is an ambient, always-on visual journal for software quality workflows. Where traditional QA tools capture a single screenshot at a moment of failure, FrameHarbor continuously weaves a rolling tapestry of frames from your desktop or device viewport, then exposes that tapestry to AI assistants through the Model Context Protocol (MCP). Think of it as a lighthouse keeper for your screen: it never sleeps, it remembers the shape of every wave, and when the storm hits, the beam of evidence is already waiting.

Built for teams who treat quality assurance as an observational science rather than a reactionary chore, FrameHarbor transforms passive screen time into structured, searchable, context-rich artifacts. Each frame is a breadcrumb; each session is a trail; each investigation is a story you can replay frame by frame alongside an AI collaborator.

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🌅 The Philosophy Behind FrameHarbor

Most observability stacks were designed for servers, not for the messy, human, pixel-driven world of front-end behavior. A backend trace tells you a function took 340ms; it will not tell you that the toast notification appeared underneath the modal, that the spinner froze at 87%, or that the cursor visibly crossed into a dead zone. FrameHarbor was born from the conviction that visual memory is a first-class debugging primitive.

The metaphor is a harbor. Ships (events) come and go, but the harbor itself persists — logging tides, weather, and the shape of every hull that passed. FrameHarbor is that harbor for your viewport. It runs quietly in the background, discards what ages out of relevance, and preserves a rolling window of frames that any MCP-aware assistant can later query with natural language.

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🧭 Table of Contents

• Core Capabilities
• Architectural Overview
• MCP Surface Area
• Feature Highlights
• Responsive and Adaptive Interface
• Multilingual Reach
• Availability and Assistance