Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Check, fix, convert and retime SRT and WebVTT captions against Netflix, BBC and DCMP limits.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
링크는 제작자의 파일로 바로 연결돼요. 우리가 보관하거나 다시 패키징하지 않아요. 파일을 열면 Claude Desktop이 설치해요.
터미널에서 이 명령어를 실행하세요
브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 GitHub 계정 markksantos 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.3.3)은 5일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 MCPB도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Fomu MCP
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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.
Kenya government form guides: checklists, draft letters, eCitizen, Huduma, timelines. Sample data.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Check SRT and WebVTT captions against a published caption standard: Netflix English, the BBC subtitle guidelines or the DCMP Captioning Key. It flags captions that read too fast, lines that are too long, too many lines, captions that stay on screen too short or too long, gaps under the minimum, overlaps and broken timestamps. It can also fix those, convert SRT to WebVTT and back, and retime a file that's out of sync.
No dependencies. Node 18+. The same checker runs in the browser, with no install and no upload, at [markstudios.com/tools/caption-checker](https://www.markstudios.com/tools/caption-checker).
$ caption-check examples/travel-vlog.srt
travel-vlog.srt: 2 of 8 captions meet Netflix English, adult programs #1 0:00.500 -> 0:03.000 Welcome back to the channel. ✗ Gap to the next caption is 0 frames at 24 fps (minimum 2) #3 0:06.600 -> 0:07.100 First, ✗ On screen 0.50 s (minimum 5/6 of a second) #4 0:07.200 -> 0:09.000 we packed water, snacks, a rain jacket and a spare battery for the cam ✗ Reading speed 41.1 characters a second (limit 20) ✗ Line 1 is 74 characters (limit 42) ...
Each limit was read on the standard's own page on 2026-10-15.
| Netflix (English) | BBC | DCMP Captioning Key | |
|---|---|---|---|
| Reading speed | Up to 20 characters a second (adult), 17 (children’s) | 160–180 words a minute | Up to 130 / 140 / 160 words a minute (lower / middle / upper level) |
| Characters a line | 42 | 37 on broadcast (Teletext) | No character count |
| Lines a caption | 2 | 2; 3 for vertical 9:16 video | No more than 2 preferred |
| Shortest time on screen | 5/6 of a second | About 0.3 s a word (advice) | 40 frames (1 second and 10 frames) |
| Longest time on screen | 7 seconds | No number | 6 seconds |
| Gap between captions | 2 frames minimum; gaps under 0.5 s closed to 2 frames | If you leave a gap, at least 1 second (advice) | No rule |
Sources: Netflix English (USA) Timed Text Style Guide · Netflix General Requirements · Netflix Subtitle Timing Guidelines · BBC Subtitle Guidelines · DCMP Captioning Key: Text · DCMP Captioning Key: Presentation Rate
How it counts. Characters include letters, spaces and punctuation, but not line breaks or formatting ( tags, {\an8} codes, WebVTT voice spans). Reading speed is characters ÷ (out-time − in-time). Words are runs of characters that hold a letter or a digit, so speaker labels and sound tags count, as DCMP asks. Gaps run from one caption's out-time to the next caption's in-time, in frames at the frame rate you give. Anything a standard words as a recommendation is reported as advice, not as a failure.
npx github:markksantos/caption-checker#v1.3.3 captions.srt
caption-check [more files] [options] -s, --standard netflix | netflix-kids | bbc | dcmp-upper | dcmp-middle | dcmp-lower (default: netflix) -f, --fps frame rate for frame-gap checks (default: 24) --vertical 9:16 video (the BBC allows three lines) --json JSON output --advice also print advice-only notes --fix write a fixed copy to (one input file) --mcp run as an MCP server on stdio
caption-check --to vtt|srt [--speakers] [--crlf] [--out ] convert caption-check --shift [--from ] | --start-at | --rate | --sync [--to vtt|srt] [--out ] retime
It exits with 1 when any caption breaks a limit, so it works as a CI check before captions ship.
--fix writes a copy with every fix that doesn't need a person: it never changes a word or an in-time.
$ caption-check examples/travel-vlog.srt --fix fixed.srt
travel-vlog.srt: 8 changes in 7 captions, written to fixed.srt #1 Out-time 0:03.000 -> 0:02.916 (to leave 2 frames before the next caption) #4 Rewrapped to 2 lines (38 + 35 characters) #5 Out-time 0:17.000 -> 0:16.100 (off an overlap, to the 7 s maximum) ... Left for a person (2): #3 Still on screen only 0.52 s (minimum 5/6 of a second) with no free time after it: merge it with a neighbor or move the next caption #4 Still reads at 40.2 characters a second (limit 20) with no free time after it: split it, condense it or move the next caption fixed.srt: 6 of 8 captions meet Netflix English, adult programs (before: 2 of 8)
Run against 300 caption files with all six standards, it never changed a word, an in-time or the number of captions, and never left more captions failing than it started with.
--to converts SubRip to WebVTT or back; the retiming flags fix captions that are out of sync with the video. Without --out, the file goes to stdout and the summary to stderr.
$ caption-check examples/travel-vlog.srt --to vtt --out travel-vlog.vtt
travel-vlog.srt: 8 captions converted from SubRip (.srt) to WebVTT (.vtt). Written to travel-vlog.vtt $ caption-check episode.srt --shift -2.5 --from 120 --out episode.synced.srt # late by 2.5 s from caption 120 on $ caption-check film.srt --rate 23.976:25 --out film.25fps.srt # timed for 23.976 fps, video is 25 fps $ caption-check film.srt --sync 1=0:04.200,640=41:12.5 --out film.synced.srt # pin two captions, stretch the rest
{\an8}-style position codes become WebVTT line/align settings and back; & and < are escaped for WebVTT and unescaped for SubRip; voice tags become "Name: " with --speakers. Whatever the other format can't hold (font colours, NOTE blocks, WebVTT position or size) is listed, not silently dropped.It uses the same reader and writer as the online SRT to VTT converter and subtitle time shifter (subtitles.js is that code, unchanged). Run on 300 caption files (34,836 captions), SRT to WebVTT and back kept every caption's timing, and a shift there and back restored every time.
const { parse, check, fix } = require('caption-checker');
const result = check(parse(fs.readFileSync('captions.vtt', 'utf8')), 'bbc', { vertical: true }); console.log(result.flagged, 'of', result.cues.length, 'captions break a limit'); for (const cue of result.cues) for (const issue of cue.issues) console.log(cue.n, issue.severity, issue.message);
const fixed = fix(fs.readFileSync('captions.srt', 'utf8'), 'netflix', { fps: 25 }); fs.writeFileSync('captions.fixed.srt', fixed.text); // also: fixed.changes, fixed.unresolved, fixed.before, fixed.after
const { convert, retime } = require('caption-checker/convert.js'); const vtt = convert(srtText, 'vtt'); // { text, from, to, captions, notes } const synced = retime(srtText, { rate: { from: 23.976, to: 25 } }); // or { offset: '-2.5', from: 120 }, { startAt: { caption, time } }, { sync: [a, b] }
check() accepts a standard id or your own standard object with the same fields as STANDARDS in index.js.
The same checks run as an MCP server, so Claude, Cursor, VS Code and other MCP clients can check a caption file mid-task. Five tools: check_captions (a file path or pasted SRT/VTT text, a standard, fps, vertical), fix_captions (the same arguments; returns the fixed file and what changed), convert_captions (SRT to WebVTT or back), retime_captions (offset, start at, frame-rate change or two-point sync) and list_standards (each limit and the page it comes from). It runs locally: no key, no network.
# Claude Code plugin (MCP server + a caption QA skill)
/plugin marketplace add markksantos/caption-checker /plugin install caption-checker@caption-checker
claude mcp add caption-checker -- npx -y github:markksantos/caption-checker#v1.3.3 --mcp
Other clients:
{ "mcpServers": { "caption-checker": { "command": "npx", "args": ["-y", "github:markksantos/caption-checker#v1.3.3", "--mcp"] } } }
The skill in skills/caption-checker/SKILL.md tells an agent which standard to pick, how to report results and how to fix a caption without changing its words. skills/caption-fixer/SKILL.md covers fixing a file: what fix_captions changes, and what to do with the captions it leaves for a person. skills/caption-converter/SKILL.md covers converting between SRT and WebVTT and working out which kind of timing fix an out-of-sync file needs.
study/ holds the code and data behind the caption reading speed study: 339,521 captions in 387 NASA videos and MIT OpenCourseWare lectures, measured with this library.
study-auto-captions/ holds the YouTube auto-caption accuracy study: automatic vs human captions on 299 videos, plus caption coverage of the most-subscribed channels.
study-dubbing/ holds the YouTube dubbing study: every audio track on 485 videos from the 97 most-subscribed channels, split into the channels' own dubs and YouTube's automatic ones.
study-video-length/ holds the YouTube video length study: durations of 2,859 latest videos and the Shorts share of 1,484 recent uploads on the most-subscribed channels.
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