Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Beschreibung vom Entwickler (englisches Original)
Hosted video editing for AI agents: cut, caption, mix and export real video. Sign in with OAuth.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Funktioniert in Claude im Web, auf dem Desktop und auf dem Handy:
https://api.cuttingfloor.ai/mcpFühre das in deinem Terminal aus
claude mcp add --transport http cuttingfloor https://api.cuttingfloor.ai/mcpIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"cuttingfloor": {
"url": "https://api.cuttingfloor.ai/mcp"
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"cuttingfloor": {
"type": "http",
"url": "https://api.cuttingfloor.ai/mcp"
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
ChatGPT verbindet sich nur mit Servern im Internet:
https://api.cuttingfloor.ai/mcpMenünamen können sich je nach Tarif und mit der Zeit leicht unterscheiden.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Die Tool-Liste dieses Servers haben wir noch nicht gelesen; wir prüfen die Endpunkte reihum.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto Mvp2o-ai bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Antwort in 555 ms (HTTP 200)
Keine Anmeldung nötig
Noch nicht geprüft; wir lesen die Tool-Liste, wenn wir den Endpunkt prüfen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 2 von 2 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft in der Cloud des Entwicklers. Du verbindest dich übers Internet, ohne etwas zu installieren, aber was du sendest, läuft über die Server des Entwicklers.
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.34.12) kam gestern in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Er verbindet sich per URL, also funktionieren auch Apps, die Remote-MCP-Server akzeptieren, zum Beispiel ChatGPT im Entwicklermodus.
In derselben Kategorie: Figma Context MCP, Claude Real Video, Figma MCP Server
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Let any LLM watch a video locally — and search everything it has ever watched.
The Figma MCP server brings Figma design context directly into your AI workflow.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
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.
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.
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.
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 machine | In the container | What |
|---|---|---|
$CUTTINGFLOOR_MEDIA (default ~/Movies) | /media/videos (read-only) | Footage. Import with {"path": "/media/videos/clip.mp4"} |
$CUTTINGFLOOR_EXPORTS (default ~/cuttingfloor/exports) | /exports | Finished exports |
Docker volume cuttingfloor-data | /data | Timelines, 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.
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.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.timeline.create with a sequence ({width, height, fps: {num, den}}).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.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.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.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.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.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.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}.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.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.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.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.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.
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>" } } } }
| Variable | Default | |
|---|---|---|
CUTTINGFLOOR_DATA | /data | Data root |
CUTTINGFLOOR_MAX_JOBS | cores ÷ 4 | Concurrent imports, exports and QA runs (sandbox jobs queue in the sandbox instead) |
CUTTINGFLOOR_HEAVY_JOBS | 1 | Concurrent 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
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