Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Tiny native Windows screen recorder with keyboard/mouse/frame sync and GIF review.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
链接指向作者自己的文件;我们不托管也不重新打包它。打开文件后,Claude Desktop 会进行安装。
在终端中运行这条命令
浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 liuminxin45 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.5.1)于3天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 MCPB。
同一分类中有:Spec Driven Development, Remote Desktop Commander, Rystic
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Start, seed, clock, inspect and diff Rystic API simulators from your agent.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
CLI-first, AI-native Windows recording with keyboard, mouse and frame synchronization.
≈3.8 MiB native EXE · No extra runtime installs · CLI First · AI Native
English · 简体中文 · Download · About
Let an AI operate software while recording its screen and keyboard/mouse events, then query, extract and trim through MCP. Built for AI-driven software tests, bug reproduction, product showcases and walkthroughs. CLI and MCP are the primary interfaces; a native capture frame is also available. No Python, Node.js, .NET or FFmpeg installation is required.
Framelet records keyboard, mouse and frame samples together by default, sharing UTC and monotonic clocks. A timeline and content-integrity manifest accompany the GIF.
Keyboard records contain down/up transitions, key codes and scan codes, not clipboard or IME-committed text. Key events can reveal typed content; visual masks are not automatic password protection. Masked mouse coordinates are omitted. Timestamps describe observed intervals, not hardware synchronization; dwell candidates do not identify UI elements.
| Capability | What it gives you |
|---|---|
| Native capture frame | Move, resize, record, pause and save; F8 control |
| Client installation + Skill | Native setup/check/uninstall, MCPB and reusable AI recording recipes |
| CLI + local MCP | Background recording while an agent operates your app |
| Reliable long recording | Numbered GIFs of at most 300 seconds, automatic rotation and checkpoint recovery |
| Keyboard/mouse/frame timeline | Locate failed steps and review action results |
| 1–60 FPS | State checks and high-rate native review; use 30 FPS for browser sharing |
| Efficient AI review | Filtered event queries, one-pass batch probes and transient-aware action intervals |
| Demo preparation | Non-invasive anchors, action sampling checks and separate trimmed candidates |
| GIF editing | Precise time cuts and playback speed changes |
| Native frame extraction | PNGs, contact sheets, timestamp probes and region comparisons |
| Privacy and guardrails | Fixed masks, scoped MCP paths, no-overwrite and resource limits |
| Isolation and integrity | Supervised capture process, content hashes and recovery markers |
Static acceptance can use 1 FPS. Use 10–15 FPS only for explicitly size-first clips where smooth motion is secondary; human-facing demos default to 30 FPS, including README GIFs. Actual sampling depends on workload.
v0.4.1 removes repeated segment checks, skips unused RGB conversions and builds candidate previews in one analysis pass. No runtime dependencies were added.
| Local MCP workload | v0.4.0 | v0.4.1 | Time saved |
|---|---|---|---|
| Probe 64 times in one recording part | 633 ms | 52.5 ms | 91.7% |
| Analyze the last 0.5 s of a 20 s GIF | 2,106 ms | 790 ms | 62.5% |
| Analyze + preview the Bilibili demo | 971 ms | 566 ms | 41.7% |
Windows, 10 alternating warm runs per version, medians. The group fixture is 64×64; the window fixture is 640×360/600 frames; Bilibili reuses the demo below. Timings exclude model inference and UI operation and depend on input/hardware. Methodology, hashes, memory tradeoffs and raw results.
The original small real recording: 620×300 · 3 seconds · 16 FPS · 15,250 bytes. This mostly static moving-marker scene is an example, not a general compression benchmark.
Start recording → scroll the real browser → stop → probe boundaries → trim idle time.
29.88 seconds → 7.63 seconds. Native region comparisons and interval jumps located boundaries with eight midpoint probes, avoiding intermediate image exports. Read the real walkthrough.
These demos predate synchronized timelines. Current releases record keyboard/mouse/frame timelines by default; the older media illustrates capture and editing.
For viewing GIFs and inspecting them frame by frame, we recommend Minimal Image Viewer.
Windows 10 2004+ / Windows 11 x64, visible desktop capture. No built-in cloud uploads or telemetry. GIF/PNG only; no audio or MP4. Agent guide · Timeline details · Changelog.
By Neo / 刘民心. Inspired by GifCam, independently implemented. MIT.