Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Turn a screen recording into agent-readable annotated keyframes. MCP server + CLI on ffmpeg.
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We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"vidin": {
"command": "npx",
"args": [
"-y",
"@teunlao/vidin",
"mcp"
]
}
}
}Run this in your terminal
claude mcp add vidin -- npx -y @teunlao/vidin mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"vidin": {
"command": "npx",
"args": [
"-y",
"@teunlao/vidin",
"mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"vidin": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@teunlao/vidin",
"mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
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These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account teunlao, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.1.0) reached the registry 3 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, First Sale Scout
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
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Turn a video into something a coding agent can actually read.
Claude Code, Codex and friends accept images, not video. So when a bug report arrives as a screen recording, the video is dead weight — someone has to watch it and retype what happened. vidin watches it instead: it converts the recording into a small set of annotated keyframes plus a written timeline, and serves them to agents over MCP.
*A 20-second recording in, six frames out: the refund panel, the 500 dialog, the retry toast, the recovery — each boxed and timestamped. (The clip is vidin's synthetic test fixture.)*
npx @teunlao/vidin — all it asks of the machine is ffmpeg; no sharp, no headless browser, no native image library.brew install ffmpeg # + yt-dlp, only if you'll pass URLs
Hook it into Claude Code:
claude mcp add vidin -- npx -y @teunlao/vidin mcp
Or in .mcp.json / ~/.codex/config.toml equivalents:
{
"mcpServers": { "vidin": { "command": "npx", "args": ["-y", "@teunlao/vidin", "mcp"] } } }
Or straight from the shell:
npx @teunlao/vidin ~/Desktop/bug.mov # → ./.vidin/bug/
npm i -g @teunlao/vidin # or put vidin on PATH for good vidin https://example.com/screencast.mp4 # downloaded with yt-dlp vidin zoom bug.mov --from 00:41 --to 00:45 --fps 6 vidin probe bug.mov
out/
REPORT.md the entry point: timeline table, what changed where, what to open manifest.json the same, machine readable sheets/ the whole video as labelled 3x3 grids (~1.3k tokens each) frames/ full-detail annotated frames
Each frame carries a red dashed box around the regions that changed since the previous kept frame, and a bottom bar with the frame number, the timestamp in the original video, the gap since the previous frame, why the frame was kept, and how much of the screen changed.
Four tools, shaped so an agent spends context in the right order:
| tool | what it does |
|---|---|
analyze_video | video → frames on disk; returns the report text and one contact sheet image |
get_frames | full-detail frames by number or time range, capped so a call can't flood the context |
zoom_clip | re-extract a narrow window at a higher frame rate — for the moment two frames don't explain |
probe_video | duration / resolution / fps / audio, cheap |
The intended loop: analyse → look at the sheet → read the timeline → open two or three frames → zoom in if the moment between them is still unclear. Opening everything up front would burn the context before knowing which second matters.
| profile | for |
|---|---|
bug-report | default — someone recorded a screen, narrated a bug, stopped |
dense | short clips where every twitch matters (24 fps analysis, up to 80 frames) |
walkthrough | long recordings; fewer frames, wider anchors |
cheap | smallest footprint, for when the context really is tight (12 frames at 1092px) |
Tuning without leaving the profile: --max-frames, --sensitivity (percent of the screen that counts as an event, lower = more frames), --fps, --width, --quality, --no-annotate, --no-sheets.
One screenshot per second turns three minutes into 180 frames of which ~90% are identical, because the person was reading, thinking or moving the mouse. Those duplicates don't cost much — they *bury* the handful of frames where something actually happened, and an agent has to look at all of them to find out which. Frame selection is a signal-to-noise problem wearing a cost problem's clothes.
vidin is event driven instead. It walks the video at 12 fps in downscaled RGB and keeps a frame only when something actually happened:
Two invariants hold whatever path a frame took:
ffmpeg ─raw RGB @12fps, 400px─ selector ──timestamps+regions── ffmpeg ──annotated WebP
one decode pass, event state machine drawbox/drawtext streamed in plain TypeScript per frame
Decoding streams two frames at a time; the selector additionally keeps the downscaled buffers of the frames it has kept so it can recompute their deltas after pruning. That is bounded by the frame budget, not by video length: ~32 MB at the defaults. All drawing is done by ffmpeg filters, which is why there is no image library in package.json.
Development runs on Bun; the runtime code itself sticks to node: APIs, which is what lets the published package run anywhere npx does.
git clone https://github.com/teunlao/vidin && cd vidin && bun install
bun test
The fixture is a synthetic screen recording with a scripted timeline — a panel, an error dialog, a toast, a recovery, and two stretches of pointer-only motion. The suite asserts that each staged event yields exactly one settled frame and that pointer motion alone yields none. test/regressions.test.ts builds its own clips and pins every failure a review has found, so a fixed bug stays fixed.
whisper.cpp or mlx-whisper) → a transcript.md aligned to the frame timeline.--sensitivity 0.2 or --profile dense catches them, at the cost of more frames.