프로토타입 · 미리 보기: 공식 레지스트리의 모든 서버를 담고 있으며 30분마다 동기화해요. 리뷰와 계정 기능은 다음 단계에서 열려요.
PopNx MCPAI를 쓰는 사람을 위한 MCP 서버 · 쉬운 말로 설명해요

cuttingfloor

제작자: Mvp2o-ai버전 0.34.12i★ –i클라우드에서 실행
레지스트리 이름io.github.Mvp2o-ai/cuttingfloor

설치

개요

제작자가 쓴 설명(영어 원문)

Hosted video editing for AI agents: cut, caption, mix and export real video. Sign in with OAuth.

PopNx MCP의 세 기둥

이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.

할 수 있는 일

이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.

  • 연결 방식: 클라우드에서 실행
  • 전송 방식: Streamable HTTP
  • 카테고리: 디자인, 이미지 및 오디오

설치

쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.

설치하기 전에

  • 기본 점검: 2개 중 2개 통과
  • 제작자의 서버에서 실행돼요. 내가 요청한 내용은 제작자의 서버를 거쳐요.
  • 레지스트리에 입력해야 할 키가 나와 있지 않아요.

필요한 것

어떤 앱을 쓰세요?

위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.

웹, 데스크톱, 모바일의 Claude에서 쓸 수 있어요:

  1. Settings → Connectors 열기
  2. Add custom connector 누르기
  3. 아래 주소를 붙여 넣고 Add 누르기
  4. 로그인하라고 하면 제작자의 서비스에 로그인하기
SettingsConnectors1+ Add2https://…3
https://api.cuttingfloor.ai/mcp

터미널에서 이 명령어를 실행하세요

claude mcp add --transport http cuttingfloor https://api.cuttingfloor.ai/mcp

Cursor에서 열기

또는 설정을 직접 복사하기

프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요

{
  "mcpServers": {
    "cuttingfloor": {
      "url": "https://api.cuttingfloor.ai/mcp"
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

VS Code에서 열기

또는 설정을 직접 복사하기

프로젝트의 .vscode/mcp.json에 붙여 넣으세요

{
  "servers": {
    "cuttingfloor": {
      "type": "http",
      "url": "https://api.cuttingfloor.ai/mcp"
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요:

  1. 웹에서 ChatGPT 열기 → Settings → Connectors (Apps)
  2. Create 또는 Add 누르기(일부 요금제는 먼저 Advanced에서 Developer mode를 켜야 해요)
  3. 아래 주소를 붙여 넣고 이름을 정한 뒤 저장하기
  4. 로그인하라고 하면 제작자의 서비스에 로그인하기
SettingsConnectors1+ Create2https://…3
https://api.cuttingfloor.ai/mcp

메뉴 이름은 요금제나 시기에 따라 조금 다를 수 있어요.

선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.

이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.

할 수 있는 일

아직 이 서버의 도구 목록을 읽지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요.

기본 점검i

누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검

  • ✓ 통과

    제작자와 저장소 일치

    레지스트리 이름이 GitHub 계정 Mvp2o-ai 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요

  • … 아직 점검 안 함

    계속 관리되고 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • … 아직 점검 안 함

    라이선스 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • ✓ 통과

    엔드포인트 응답

    555ms 만에 응답(HTTP 200)

  • – 해당 없음

    OAuth로 로그인

    로그인 필요 없음

  • … 아직 점검 안 함

    도구 설명에 숨겨진 지시 없음

    아직 점검하지 않았어요. 엔드포인트를 점검할 때 도구 목록을 읽어요

디자인, 이미지 및 오디오 카테고리의 다른 서버와 비교i

  • 이 카테고리의 다른 서버 2204개 중 0%보다 스타가 많아요
  • 이 카테고리의 다른 서버 2204개 중 98%보다 최근에 레지스트리에 공개됐어요
  • 기본 점검 결과가 이 카테고리의 다른 서버 2204개 중 100%와 같거나 더 좋아요

레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.

자주 묻는 질문

cuttingfloor, 안전한가요?

해당하는 기본 점검 2개 중 2개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.

어떤 키나 코드가 필요한가요?

레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.

내 컴퓨터에서 실행되나요, 클라우드에서 실행되나요?

제작자의 클라우드에서 실행돼요. 설치 없이 인터넷으로 연결하지만, 보내는 내용은 제작자의 서버를 거쳐요.

아직 관리되고 있나요?

GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.34.12)은 어제 레지스트리에 올라왔어요.

어떤 앱에서 쓸 수 있나요?

Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. URL로 연결되기 때문에, 원격 MCP 서버를 지원하는 앱(예: 개발자 모드의 ChatGPT)에서도 쓸 수 있어요.

대신 쓸 수 있는 건 뭐가 있나요?

같은 카테고리에는: Figma Context MCP, Claude Real Video, Figma MCP Server

대안

같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.

카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i

Figma Context MCP

제작자: GLips

Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.

내 컴퓨터에서 실행★ 16,165MIT5개월 전 업데이트
설치

Claude Real Video

제작자: HUANGCHIHHUNGLeo

Let any LLM watch a video locally — and search everything it has ever watched.

내 컴퓨터에서 실행★ 2,284MIT2개월 전 업데이트
설치

Figma MCP Server

제작자: figma

The Figma MCP server brings Figma design context directly into your AI workflow.

클라우드에서 실행★ 2,15213개월 전 업데이트
설치

제작자의 README

README 열기

제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.

cuttingfloor

A headless video editor for agents, as an MCP server. An agent imports footage, cuts it on a timeline with granular editing tools, looks at the result after every edit, checks it, and exports a file.

  • Every edit returns a new timeline id, plus a preview image of the result. Timelines are immutable, so going back is just using an older id.
  • Nothing is stored for you. Timelines, media and outputs live in a cache with a time limit (24 hours for timelines, 7 days for media and exports). Export to keep work.
  • One Docker image runs locally (free) and hosted. Engines (FFmpeg, MLT) ship inside it; Docker is the only thing you install.

What it covers: import, cutting on words, timing, transitions, titles and captions, audio, effects, analysis (transcripts, beats, faces, tracking, scenes), compositing, motion graphics and stills from HTML, voiceover, cut-outs, stems, stabilizing, upscaling, lip-sync, previews, QA checks, and export to MP4, ProRes, GIF and audio or to Final Cut, Premiere and Resolve (FCPXML, OTIO, EDL). Every tool: cuttingfloor.ai/features. Use it from Kazi, Claude, ChatGPT or any MCP app.

Use it hosted

Sign up at cuttingfloor.ai (three days free), then add https://api.cuttingfloor.ai/mcp as a remote MCP server in Claude, ChatGPT, Cursor, Kazi or any client that takes one. The client opens the sign-in itself (OAuth). Nothing to install; transcription, voiceover, cutouts and rendering run on our servers. The official MCP Registry entry lists the same address.

Run it yourself

docker compose up -d          # local mode: one node on 127.0.0.1:8787, plus the motion sandbox

Compose starts two containers from the same image: cuttingfloor (the server) and cuttingfloor-motion, the sandbox where agent-written HTML for create.motion and create.still renders. The sandbox has no route out, no data volume, no capabilities, a read-only filesystem and fixed CPU, memory and process limits. Chromium's own sandbox stays on inside it, using the seccomp profile at tools/motion/seccomp.json (Docker's default plus namespace creation). Run compose from a checkout of this repository so that file is there.

Connect an MCP client over Streamable HTTP:

{ "mcpServers": { "cuttingfloor": { "url": "http://127.0.0.1:8787/mcp" } } }

Or over stdio, for clients that only launch commands. The stdio process forwards to the running container, so long exports keep going after the client exits:

{ "mcpServers": { "cuttingfloor": { "command": "docker", "args": ["exec", "-i", "cuttingfloor", "cuttingfloor", "mcp"] } } }

Folders (set them in a .env next to compose.yaml, see .env.example):

On your machineIn the containerWhat
$CUTTINGFLOOR_MEDIA (default ~/Movies)/media/videos (read-only)Footage. Import with {"path": "/media/videos/clip.mp4"}
$CUTTINGFLOOR_EXPORTS (default ~/cuttingfloor/exports)/exportsFinished exports
Docker volume cuttingfloor-data/dataTimelines, proxies, jobs (with time limits)

Provider keys are yours (bring your own) and go in the same .env, or in Docker secrets (/run/secrets/ ). They never pass through a tool, and video://server/health shows only whether each is set. create.lipsync needs SYNC_API_KEY from sync. labs (Settings → API keys); they bill your account for each second sent. Run docker compose up -d after adding one.

The image includes /samples/sample.mp4 (10 s test pattern with a tone) and /samples/card.png to try things with nothing mounted.

On Docker Desktop for Mac, raise the memory limit for long 4K timelines; bind-mounted footage reads go through VirtioFS. On Linux, create the exports folder before the first start so it belongs to you.

How an agent uses it

  1. media.import each file. It's long-running: a task for clients that support MCP Tasks, otherwise a job_id to poll with job.get. The media_id is usable once the job reports processing.
  2. media.analyze turns media into data an agent can edit with: transcript (every word with its time; whisper.cpp on the CPU, the model downloads once), beats (tempo, beats, downbeats), faces (face boxes over time) and track (follow a region). Then cut by words with clip.add {source: {words: [i, j]}} and caption with caption.add {in_clip: {clip_id, segments}}, timed in the media's seconds. media.seek finds moments from plain words, so an agent doesn't have to watch the whole video: give it criteria like {too_dark: "the faces are too dark to make out their eyes", demo: "the product dashboard fills the screen"} and it returns the stretches of a video, or of an edit as it renders, where each one holds, with the best frame of each. Use it to check quality, find where something starts, pick shots, spot changes or find room for a title. TypeSafe Jev judges the frames and needs TYPESAFE_API_KEY.
  3. timeline.create with a sequence ({width, height, fps: {num, den}}).
  4. Edit: clip.add, clip.trim (with side for J/L cuts), clip.split, clip.move, clip.remove (with ripple), clip.link, track.*, or edit.batch to apply many edits at once, using {"$ref": "ops[0].clip_id"} for ids made earlier in the batch.
  5. Time: clip.set_speed (constant rate, a speed-ramp curve, reverse; pitch is kept), clip.freeze, clip.roll, clip.slip, clip.slide, clip.replace, and range.extract / range.lift to cut a span out of every track at once. clip.add {nested_timeline_id} nests a whole timeline as one clip.
  6. Transition: transition.add at the cut after a clip: dissolve, dip to black or white, wipes, slides, pushes, zooms, iris and spin. Linked audio crossfades at the same cut. By default the clips overlap and later clips move earlier; mode: "handles" uses source past the cut and moves nothing.
  7. Text: title.add and caption.add (from segments with word timings, or from SRT/VTT) put text on a video track, rendered with libass: font, size, colour, outline, shadow, box, karaoke and word highlights, typewriter and word reveals. text.set restyles many at once. Fonts are listed at video://catalog/fonts; import your own .ttf/.otf with media.import and use it with font_media_id.
  8. Audio: audio.set_gain (dB, with keyframes for rides), audio.set_pan, audio.fade and audio.set_master (gain and a limiter ceiling on the whole mix). Audio edits preview as a waveform image with the measured loudness.
  9. Effects: filter.add on a clip, every clip on a track, or the whole timeline: colour (brightness, contrast, saturation, exposure, temperature, curves, LUTs imported as .cube), blur, sharpen, vignette, grain, glitch, pixelate, chroma key; for sound EQ, compressor, noise reduction, de-esser, dialogue enhance, reverb, echo, pitch. adjustment.add adds a clip whose effects change everything below it while it runs. The list with params is at video://catalog/effects.
  10. Composite: put a clip on a higher video track, then clip.set_transform (position, scale, rotation, opacity, crop, flip, fit; any number can take keyframes with easing), clip.set_mask (rectangle, ellipse, linear, mirror, heart, star, polygon), clip.set_blend and clip.set_animation (entrance, exit and loop presets). The accepted names are resources at video://catalog/{name}.
  11. Create: create.motion renders any animated HTML to a video with alpha, frame-exactly: CSS animations and transitions, the Web Animations API, SVG, canvas or WebGL drawn in requestAnimationFrame, timers, or a window.__seek(seconds) the page defines all run on a virtual clock the renderer steps one frame at a time. anime.js, three.js, Lottie and D3 load from lib/ ( ). create.still renders an HTML page to a PNG, and create.matte makes a solid or gradient picture. Each returns a media_id for clip.add; the same recipe returns the same media. Pages can't reach the network, so images and fonts go in as assets (imported media) and are referred to as assets/ . create.voiceover speaks English text in one of 28 Kokoro voices on the CPU (the model, about 350 MB, downloads once) and times every word, so caption.add {in_clip} can caption it exactly. create.cutout removes the background behind a subject: any (BiRefNet; products, animals, objects, people; the default for pictures; needs about 3 GB of memory free for Docker) or people (MODNet; fast enough for video, the default there), keeping the sound. create.lipsync makes someone on camera say new words: give the video, the new speech (a re-recorded line or a voiceover) and the span of the video to change, and their mouth is redrawn to match by sync. labs on your own key (SYNC_API_KEY locally, the X-Cuttingfloor-Key-Sync header hosted). Only the span is sent; the result is that span, to place over the original.
  12. Look: preview: "inline" on any edit returns the image; render.frames returns up to 16 frames as a contact sheet, or up to 4 at full size (size: "full") for thumbnails.
  13. qa.check measures the render: gaps, offline media, frame count, loudness and true peak, plus black and silent stretches with the settings you give. Facts, no verdicts.
  14. export.video with a preset: web_1080p_h264, master_prores_422hq, social_9x16_h264, web_1080p_av1, gif, audio_wav_48k or audio_mp3, and overrides for size, frame rate, bitrate or quality (video://catalog/presets). The result has a signed download URL and, locally, the file in your exports folder.
  15. export.timeline hands the edit to another editor as FCPXML (Final Cut Pro, Resolve), OTIO (Premiere, Resolve) or a CMX 3600 EDL, or writes the captions as SRT or VTT, with warnings for what the format can't carry. media: "collect" zips the media alongside. timeline.get stays the lossless copy.

Time is integer frames at the sequence rate, end-exclusive. timeline.get returns the whole timeline as JSON; timeline.load restores it after it expires. video://server/health reports engine versions and limits.

Hosted mode

The same image with CUTTINGFLOOR_MODE=hosted: no path imports (URLs only), no exports folder, and every request needs Authorization: Bearer from CUTTINGFLOOR_API_KEYS (owner:key,owner2:key2, or the cuttingfloor_api_keys Docker secret). Each key's owner has separate timelines, media and jobs. CUTTINGFLOOR_PUBLIC_URL is required: download links are built from it, and the server won't start without it.

Provider keys hosted come from the client, never from the server's environment: the MCP client sends each one as a header in its server config, X-Cuttingfloor-Key- , for example X-Cuttingfloor-Key-Sync: for create.lipsync. The key is used for that request and the job it starts, then dropped; it is never stored or logged. A tool that needs a key you haven't sent answers credential_required, naming the header.

{ "mcpServers": { "cuttingfloor": { "url": "https://api.cuttingfloor.ai/mcp", "headers": { "X-Cuttingfloor-Key-Sync": "<key>" } } } }
VariableDefault
CUTTINGFLOOR_DATA/dataData root
CUTTINGFLOOR_MAX_JOBScores ÷ 4Concurrent imports, exports and QA runs (sandbox jobs queue in the sandbox instead)
CUTTINGFLOOR_HEAVY_JOBS1Concurrent create.cutout and create.stems runs, in their own slots apart from the jobs above

| CUTTINGFLOOR_SHORT_JOBS | 1 | Extra job slots only short jobs take (an analysis, check or export of at most `CUTTINGFLOOR_SHORT_JOB_SE

앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요

PopNx에게 묻기