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cuttingfloor MCP Server

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cuttingfloor is answering right now. Last checked 2 min ago. It exposes 71 tools. Last commit 24 Oct 2026.

Video editing for AI agents: cuts, captions, audio, motion graphics, previews, and exports.

Uptime history 7 days of history
7 days agonow
100.0%
Uptime 24h
92 of 92 checks
71
Tools
read from the server
480 ms
Response time
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0
Stars
last commit 24 Oct 2026

What changed 1

Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 25 October 2026. No other catalogue keeps this.

25 Oct a tool changed version

What the code does

We read the source, 1 h ago · tools taken from the live server · rules 995398eba69f

Capabilities

What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.

Image runs as root Dockerfile:267
USER root
Secret passed into the image build Dockerfile:109
ARG CLAP_TOKENIZER_SHA256=dc239041d98de27ffc3975473a1a23e3db4c937b23c138c38bbc66588bd247e5
Page executes code built at runtime packages/server/src/player.html:308
    t.innerHTML = `<svg viewBox="0 0 24 24" aria-hidden="true"${cls ? ` class="${cls}"` : ''}>${body}</svg>`;

Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.

This code can reach further than it looks

We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.

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Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 2 min ago.

run in your terminal
claude mcp add cuttingfloor --transport http https://api.cuttingfloor.ai/mcp
Settings → Connectors → Add custom connector, then paste this address
https://api.cuttingfloor.ai/mcp
~/.codex/config.toml
[mcp_servers.cuttingfloor]
url = "https://api.cuttingfloor.ai/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "cuttingfloor": {
      "url": "https://api.cuttingfloor.ai/mcp"
    }
  }
}
.vscode/mcp.json
{
  "servers": {
    "cuttingfloor": {
      "type": "http",
      "url": "https://api.cuttingfloor.ai/mcp"
    }
  }
}

Available tools 71

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

clip
clip.add
Place media on the timeline. A/V media lands as a linked pair on a video and an audio track. Default: the whole media, after the last clip, overwriting. A picture is scaled to fit the frame (a small logo fills it edge to edge); clip.set_transform {fit: "none"} keeps its own pixel size. Returns the edit result (see the server instructions).
clip.freeze
Hold the frame at at_frame for duration_frames: the clip splits there, a freeze frame goes in, and later clips on its tracks move later. Freezing a clip's last frame holds it after the clip, with silence under the hold. Returns the edit result (see the server instructions).
clip.link
Make clips move, trim and split together. Returns the edit result (see the server instructions).
clip.move
Move a clip (and its linked clips) to a frame and optionally another track. Returns the edit result (see the server instructions).
clip.remove
Remove a clip and the clips linked to it; ripple closes the gap. Returns the edit result (see the server instructions).
clip.replace
Swap the media in a clip, keeping its place, length, speed and look. Starts at source_in (default 0). Returns the edit result (see the server instructions).
clip.roll
Move the cut between a clip and the clip right after it: one gets longer, the other shorter, nothing else moves. Returns the edit result (see the server instructions).
clip.set_animation
Entrance, exit and loop presets layered over the clip transform (video://catalog/animations): e.g. in {name: "pop", duration_frames: 12}, loop {name: "float"}. null removes one. Returns the edit result (see the server instructions).
clip.set_blend
How a video clip mixes with the tracks below: normal, multiply, screen, overlay and more (video://catalog/blend_modes). Returns the edit result (see the server instructions).
clip.set_enabled
A disabled clip stays on the timeline but renders as a gap. Returns the edit result (see the server instructions).
clip.set_mask
Show only part of a video clip: rectangle (rounded), ellipse, linear, mirror, heart, star or polygon, with feather and invert. Position, size, rotation and feather animate like transform values. null removes the mask. Returns the edit result (see the server instructions).
clip.set_speed
Speed up, slow down, ramp or reverse a clip and its linked clips. rate is constant; curve is a speed ramp over the clip. The clip keeps its source and its length changes; ripple (default) moves later clips. Pitch is kept unless preserve_pitch is false. Returns the edit result (see the server instructions).
clip.set_transform
Position, scale, rotate, fade, flip, crop or fit a video clip over the tracks below (picture-in-picture, overlays, punch-ins). fit none shows a graphic at its own pixel size, so scale 1 is its real size; the default contain scales it to touch the frame edges. Any number takes a constant or {keyframes: [{frame, value, ease}]} with frames from the clip start; eases are listed at video://catalog/eases. Omitted fields keep their value; null resets one. To pin an overlay to a moving subject, use media.analyze track boxes as keyframes: for each box, frame = timeline frame of the box time (where the tracked clip plays that media second) minus this clip's start, x = box x + w/2 and y = box y + h/2 (add your offset). That holds when the tracked clip fills the frame as is; if it is scaled, moved or cropped, map the box through its transform first. Skip boxes with found false. Returns the edit result (see the server instructions).
clip.slide
Move a clip between its neighbours: the clip before it and the clip after it change length so nothing else moves. Returns the edit result (see the server instructions).
clip.slip
Show earlier or later source in a clip without moving or resizing it. Returns the edit result (see the server instructions).
clip.split
Cut a clip (and its linked clips) in two at a frame. Returns the edit result (see the server instructions).
clip.trim
Move the start or end edge of a clip. side: video or audio trims one half of a link group (J/L cuts). Returns the edit result (see the server instructions).
clip.unlink
Break the link group a clip belongs to. Returns the edit result (see the server instructions).
media
media.analyze
Find what is in imported media, or in the sound of an edit, as data for edits. transcript: every word with its time (whisper.cpp on the CPU; the model downloads once). For English the word edges are then aligned to the sound (wav2vec2 forced alignment): a word starts and ends within about 0.05 s of where its letters sound, and an end on a soft consonant (s, t, k, f) or a breath can ring on up to about 0.1 s more; timing_confidence says how clearly each word was heard. Other languages keep whisper's own times, up to about a second off. Short ums and uhs are often left out of the words; kind speech still hears them. beats: tempo, beat and downbeat times. faces: face boxes over time, e.g. to reframe to 9:16 with clip.set_transform keyframes. track: follow a region you give from a moment on, a box for each sampled time (found false where the subject was lost); to make a title, sticker, arrow or mask follow the subject, turn the boxes into clip.set_transform (or clip.set_mask) keyframes, no tracking of your own needed. look: your own typed questions about what is on screen, answered on every sampled frame (to find where something happens from plain words, media.seek). silence: stretches quieter than threshold_db for at least min_seconds. scenes: times the picture changes by more than threshold (0–100). speech: the probability that someone is speaking, every 32 ms (Silero VAD), and the spans where it is at least your min_probability; it hears speech, not noise or music, so a cough or a door is not speech. loudness: integrated loudness (LUFS), true peak (dBTP), loudness range (LU), RMS level and noise floor (dBFS) over the whole media or from_seconds to until_seconds. To line up two recordings, media.correlate. sounds: what can be heard and when, every 40 ms, for 447 named sounds (video://catalog/sounds: Laughter, Applause, Cough, Sneeze, Music, Speech, Door, Footsteps, Beep…): give labels for the ones you want, or none for every sound that reaches your min_probability; you get each sound's spans and its probability in every frame (a run over the whole media is kept with it; one over from_seconds to until_seconds comes back only). To find a sound you describe in your own words, media.listen. With timeline_id instead of media_id, speech, loudness, silence, sounds measure the edit's mix as it plays, over from_seconds to until_seconds (timeline seconds). A source or range with no sound fails with no_audio, naming it. Times are media seconds (timeline seconds for a timeline); boxes are fractions of the picture. Results stay with the media (media.get include) except track, silence, scenes and loudness, which come back in the result; speech over the whole media is kept (media.get include speech), so asking again with another min_probability or range answers from it. A result too long to return (a long transcript) comes back as its summary and a note: read it in pieces with media.get include and a time range or page. Long-running: returns a task, or a job_id for job.get. HOW LOOK WORKS. TypeSafe Jev, a fast judgment model (preview), answers your questions about frames sampled from the media. Each sampled frame is its own request: Jev sees that one picture, named `frame`, and with with_previous also the frame sampled just before it, named `previous`, plus any state you give: text or JSON entries by name, the same on every frame (the script, what a term means). Every question is answered on every frame, independently and in parallel (about 0.15 s a frame), as typed data you then combine in your own code. Choose the type by the answer you need. noul: yes or no, answered as noul, the probability of yes from 0 to 1. choice: one of options you name, answered as choice plus probabilities and confidence. score: a degree on levels you order, answered as score (0 is the first level; it can land between levels) plus confidence. box: where one thing is, answered as box {x, y, w, h} in fractions of the picture plus confidence. Write each question about the picture as it looks. Name the picture in backticks ("in `frame`"), ask about one thing, word it so yes means the thing is there, and describe it as it appears: "Does `frame` show a human being, even if only their face fills the picture?", "Is one large word laid over `frame`, much bigger than any other text?". To compare, name both pictures and the thing that differs: "Is there a button in `frame` that is not in `previous`?". To locate, name the one thing so only it fits ("the 'Get started for free' button under the headline in `frame`") and, in the same call, a noul asking whether it is there; use the box on frames where that noul is high. Give a choice a none option for frames where nothing fits, and each score level a concrete situation. Read the answers this way: a noul of 0.5 or more reads as yes, and you can set your own cut-off; confidence tells you how far to trust a choice, a score or a box, and a loose box shows as low confidence. Work in passes: every_seconds 1 over the whole media, then at_seconds around the times where answers change. media.get scenes give when the picture cuts; look tells you what is on it. The result gives each question's spans (when a noul reads yes, which choice holds when); every frame's answers stay with the media (media.get include ['look'], the last 10 runs). Up to 600 frames and 32 questions a call. To find the moments that match a description, media.seek takes it in plain words and returns where it holds. For one judgment about text, a still or a single frame, judge.ask answers at once. Full guide to writing questions: https://docs.typesafe.ai/primitives and https://docs.typesafe.ai/images.
media.correlate
Find how far one recording sits from another: the sync offset of b against a, by cross-correlating their sound, with how strongly they match. Use it to line up a camera with a separate microphone, two cameras of the same moment, or a re-recorded line against the original. Each side is imported media or an edit's mix (timeline_id), over its own from_seconds to until_seconds, so you can match a short stretch of b against a longer stretch of a. offset_seconds: b's moment t lines up with a's moment t + offset_seconds, each in its own seconds. To line them up on a timeline, place b's clip so it starts offset_seconds later than a's (earlier when negative), source starts being equal. strength is the correlation of the overlapping sound at that offset, -1 to 1: near 1 the same sound, near 0 unrelated; next_best is the best offset outside the winning peak, and a strength close to it means the match is unclear (repetitive sound, or not the same moment). Offsets are searched up to max_offset_seconds either way, where at least half of the shorter sound overlaps the other. Up to 600 s read from each side. A side with no sound in its range (no audio stream, a range past its end, or digital silence) fails with no_audio, naming which side. Short reads answer at once; longer ones return a task or job.
media.delete
Delete a media for good, so an old or wrong version stops turning up: its file here, proxy, mezzanine and media.analyze results go, and its room comes back to the storage cap. A path import leaves the original in its folder; exports made from it stay. Timelines that use it keep their ids and edits but no longer render (media_offline names it, as for expired media): replace those clips with clip.replace. Importing the same file again makes a new media_id.
media.get
Status, where it came from (origin: the import source, the export of which timeline_id and preset, or the create.* tool and the media it was made from), a signed download url for the file (media is kept 7 days after last use: save the file from it to keep it, and media.import it again later) and a page_url that plays or shows it in any browser (to give a person), its format (extension and mime_type, read from the file, not its name), everything the probe read (probe: the format and every stream, e.g. pix_fmt, colour space, primaries, transfer), duration, frame rate, conform reasons, integrated loudness and summaries of media.analyze results under analyses (counts only: analyses.transcript.words is how many words). include returns those results at the top level, e.g. include ["transcript"] gives transcript.words, the list of words with times. For long media, read them in pieces: from_seconds and to_seconds keep what overlaps that stretch of the media, offset and limit page through what is left, and pages says, per analysis, the index of the first item returned in the whole list (for transcript words, the index clip.add source {words} takes), how many matched and next_offset for the next page (null at the end).
media.import
Import the user's own video, audio, image or font to edit with or place as is: probe, fingerprint, conform if needed (VFR, rotation, HDR → BT.709), 540p proxy and integrated loudness. A reference image to recreate needs no import: rebuild it with create.motion or create.still. Long-running: returns a task, or {job_id, media_id} for job.get. The media_id is usable in edits as soon as the job reports processing, so with many files, start every import first and edit while they finish. Sources: an http(s) URL (Dropbox and Google Drive share links work as they are), {upload: {name, bytes}} for a file you send yourself (the answer is the new media with upload.url: PUT the file there, curl --fail -T file '<url>', and it imports once the last byte arrives, with no base64 in a message; a broken PUT resumes as media.upload says), the upload_id of a file sent through media.upload, a small file as a data: URI (up to 8 MB, with its sha256 so a garbled copy is refused), or the job_id of a completed export.video (its render becomes media). A URL is fetched once, when the import starts: it only has to work until then (a short-lived signed link from the user's own storage is enough), and the copy stays here 7 days after last use. A file the user attached in the chat comes as file, when the client passes it. Importing the same file again returns the same media_id.
media.list
What the user has here: imported and created media, and files they sent that aren't imported yet (through media.upload, or dropped on their account page at cuttingfloor.ai/account), with names, sizes and when each expires, plus the account's storage used and its cap. When the user mentions a file they sent or dropped ("the interview I uploaded"), find it here by name and media.import {source: {upload_id}} it; complete says it is all in. Listing does not count as a use, so nothing here lasts longer for being listed.
media.listen
Find when something can be heard in a video or audio file, or in an edit as it plays, from what you describe in plain words, so you go straight to it instead of listening to it all: laughter, applause, a cough, a door slamming, a phone ringing, a dog barking, music starting, someone typing, a car passing. Name each sound and say what it is; you get back the stretches of time where each one can be heard, with the moment it is clearest. Use it to: - Find reactions and moments: where the crew or the audience laughs, where people clap or cheer, a gasp, a scream. - Find trouble to cut or cover: a cough, a sneeze, a phone going off, a door, a siren, wind on the microphone, a click or a bump. - Find sound to cut on: a clap, a bang, a hit, the music starting or stopping. HOW IT WORKS. FlexSED, an open-vocabulary sound detection model (local, on the CPU; about 15 to 20 times faster than real time), listens to every 40 ms of the sound and gives each description the probability that it can be heard there. Describe the sound itself, briefly, as you would caption it ("laughter", "a crowd cheering", "glass breaking"), not the scene or a judgment; it is asked as "The sound of <your words>". Short, common sound names work best; put each sound you want in its own entry, up to 16 a call, all listened for at once. READING THE RESULT. matches gives, per sound, each run of frames at or above min_probability (default 0.5) with its start, end, peak_seconds and frame (for render.frames; media frames for video, timeline frames for an edit). peaks gives the highest probability each sound reaches, and scores every probability (step_seconds apart), for your own cut-off. A sound whose peak stays well under your cut-off is most likely not there; one hovering near it is worth a listen or a lower cut-off. Media or an edit: with media_id, times are the file's own seconds; with timeline_id, it listens to the edit's mix as it plays (cuts, gaps, levels and effects included), over from_seconds to until_seconds, and times are timeline seconds, so a match is where that sound now sits in the edit. A source or range with no sound fails with no_audio, naming it. For the 447 sounds with names (Laughter, Applause, Cough, Speech, Music…) as stored data, media.analyze kind sounds. Long-running: returns a task, or a job_id for job.get.
media.seek
Find the moments in a video, or in an edit as it renders, that match what you describe in plain words, so you go straight to them instead of watching it all. Name each criterion and say what a matching frame shows; you get back the stretches of time where each one holds, with the time and picture of the best frame in each. Use it to: - Check quality: find frames that are too dark or blown out, out of focus, black or blank (a gap in an edit), with a microphone or crew in shot, with text cut off at the edge, or with a caption over a face. With timeline_id it checks the edit as it renders, titles, effects and gaps included. - Watch efficiently: looking through a whole video costs you a picture for every moment. Seek judges the frames for you and says where things are, so you look only there: where the demo starts, where the speaker holds up the product, where the second location begins. - Pick shots: B-roll or a thumbnail moment that fits a description ("a wide shot of a city street at night", "she smiles straight at the camera with her eyes open"). - Find changes: with with_previous, where the slide changes, someone walks in or the camera angle switches ("`frame` shows a different slide from `previous`"). - Find room or trouble for overlays: where the lower third stays empty for a title, or where a logo, a licence plate or a face appears that needs a blur. HOW TO WRITE CRITERIA. TypeSafe Jev, a fast judgment model (preview), judges each sampled frame on its own, as a picture named `frame` (about 512 px on its long edge; with with_previous also `previous`, the frame sampled before), and gives each criterion the probability that it is true. A criterion is a statement or a question about how the picture looks. Keep one judgment to a criterion, and say what shows rather than a verdict: not "bad lighting" but "the faces are too dark to make out their eyes"; not "a good thumbnail" but "a person looks straight at the camera with eyes open and mouth closed". Criteria that name no picture or state entry in backticks are asked about `frame` ("In `frame`: <your words>"); name `frame`, `previous` or your state entries yourself to judge them together ("`frame` shows the button `line` talks about"). Jev answers most accurately from examples: give {instructions, criteria: {true: "…", false: "…"}} with a case of each ({true: "the face is a dark silhouette against a bright window", false: "the face is evenly lit, a little dim"}). Detail too small to see at that size (fine print, slight softness) answers poorly; check it with render.frames at full size. READING THE RESULT. matches gives, per criterion, each run of consecutive samples at or above min_probability (default 0.5), with its start, end and best sample: peak_seconds, frame (for render.frames) and uri (a resource to read the picture). samples has every probability, for your own cut-off. A probability near 0.5 means Jev cannot tell, not that the thing is half there: reword a criterion that keeps landing there. asked shows the question each criterion became. COST. Each frame is one judgment however many criteria it carries, so ask everything you are looking for in one call (up to 32 criteria). Work in passes: every_seconds 2 to 5 over the whole video, then at_seconds around a match to find more exactly where it starts. Up to 600 frames a call. Long-running: returns a task, or a job_id for job.get. media.analyze look asks typed questions (a choice, a score, a box) of every frame when you need measurements rather than moments; judge.ask judges one picture at once.
media.upload
A signed URL to send one of the user's files to this server, for files on their machine that the server can't read: PUT the file there (curl --fail -T interview.mp4 '<url>'), then media.import {source: {upload_id}}. The URL needs no other credentials and works for a day. A broken upload resumes: HEAD the url for Upload-Offset (the bytes received), then PUT the rest with Content-Range: bytes <offset>-<last>/<total>. Large files can go in parts the same way. Without a way to send it yourself, give the user the url: opened in a browser it is a page to drop the file on, which sends it and resumes on its own. media.import says whether the file is all in yet.
timeline
timeline.create
Start an empty timeline. Returns its timeline_id and its tracks (ids for track_id). Timelines are immutable: every edit returns a new timeline_id, and older ids stay valid for 24 hours after last use. For work longer than a day, keep the timeline.get document on your side and restore it with timeline.load.
timeline.diff
Which clips, tracks and settings differ between two timelines.
timeline.get
The full timeline: tracks, clips (frames, end exclusive), link groups and the media it uses. The server keeps a timeline 24 hours after last use: for work longer than a day, save this document on your side (it is the edit) and restore it with timeline.load.
timeline.history
The chain of edits that made this timeline, newest first. To go back, keep using an older timeline_id.
timeline.load
Restore a timeline from the document timeline.get returned, e.g. after it expired (24 h after last use). Its media must still be here: media expires 7 days after last use, so import saved files again with media.import and swap them in with clip.replace.
timeline.set_sequence
Change resolution, frame rate or audio format. Clip times are kept in time, so they survive a rate change. Returns the edit result (see the server instructions).
audio
audio.fade
Fade a clip's sound in from its start and out to its end. null removes a fade. Returns the edit result (see the server instructions).
audio.set_gain
Volume of an audio clip (or a video clip's linked audio) in dB; keyframes ride it up and down. The preview is a waveform of the clip with the measured loudness. Returns the edit result (see the server instructions).
audio.set_master
Gain (dB) and limiter ceiling on the whole mix. The ceiling caps sample peaks (dBFS); the true peak between samples can land above it, most on dense, bright sound, and qa.check measures it (dBTP). Audio edits preview with the measured loudness. Returns the edit result (see the server instructions).
audio.set_pan
Place a clip's sound left (-1) to right (1). Returns the edit result (see the server instructions).
filter
filter.add
Apply an effect from video://catalog/effects (colour, LUT, blur, vignette, chroma key, glitch; EQ, compressor, denoise, pitch and more) to a clip, every clip on a track, or the whole timeline. Number params take keyframes. Returns its id as clip_id. Returns the edit result (see the server instructions).
filter.remove
Take an effect off. Returns the edit result (see the server instructions).
filter.set
Change an effect's params (merged) or turn it off and on. Returns the edit result (see the server instructions).
job
job.cancel
Stop a running job. Finished jobs are left as they are.
job.get
Status, progress and, once completed, the result of long-running calls (media.import, media.analyze, create.*, export.video, qa.check). Same record as tasks/get. status_message says what it is doing, or, while it waits, where it stands in the queue and what it waits for. It answers at once with where each job stands. job_id reads one job; job_ids reads many in one call and answers {jobs, not_found}.
job.list
Your recent jobs, newest first.
track
track.add
Add an empty video or audio track. New video tracks go on top. Returns the edit result (see the server instructions).
track.remove
Remove a track and its clips. Returns the edit result (see the server instructions).
track.set
Rename, mute (audio), hide (video) or lock a track. Returns the edit result (see the server instructions).
transition
transition.add
Transition at the cut after a clip, into the clip that touches it (video://catalog/transitions). Linked audio gets a crossfade at the same cut. kind crossfade is sound only: on a video clip it crossfades the linked audio and the picture cuts hard (use mode handles for that). mode overlap (default) overlaps the clips and moves later clips earlier; handles uses source past the cut and moves nothing. changed lists each transition added, with its track and kind. Returns the edit result (see the server instructions).
transition.remove
Remove a transition; the cut becomes a hard cut. Returns the edit result (see the server instructions).
transition.set
Change a transition's kind or duration. Returns the edit result (see the server instructions).
export
export.timeline
Write the edit for another editor: fcpxml (Final Cut Pro, DaVinci Resolve), otio (Premiere, Resolve, OpenTimelineIO apps), edl (CMX 3600, one video track), or srt/vtt (the captions). Best effort: warnings lists what the format could not carry (masks, blend modes, effects, animated transforms, ramps, text styling). timeline.get is the lossless copy. media collect makes a .zip with the media files next to the timeline file. Long-running: a task, or {job_id} for job.get; the result has a signed download URL.
export.video
Render the timeline to a file. Presets: web_1080p_h264 (MP4, fits 1920x1080), master_prores_422hq (MOV, sequence size), social_9x16_h264 (9:16 sequences, 1080x1920), web_1080p_av1 (MP4, AV1/Opus), gif (640 px, 15 fps), review_h264 (MP4, fits 854x854 with sound: small and quick, to watch a cut), audio_wav_48k, audio_mp3. overrides changes size, fps, bitrate or crf (video://catalog/presets). Long-running: returns a task, or {job_id} for job.get. The result links the file (a resource_link to video://jobs/{job_id}/output, which reads as the file, or its signed URL when large), has a signed download URL and a page_url that plays it in any browser (the link to give a person to watch or share), both working for 24 h (job.get gives fresh ones) . The server keeps the file 7 days: to keep it longer, save it from the url, and media.import it to use it again. qa.check measures a render (gaps, frames, loudness) before you export.
range
range.extract
Remove everything in a frame range on the given tracks (default all unlocked) and close the gap. For cutting out silences, filler words or mistakes across all tracks at once. Returns the edit result (see the server instructions).
range.lift
Remove everything in a frame range on the given tracks (default all unlocked), leaving a gap. Returns the edit result (see the server instructions).
skills
skills.get
The whole skill as Markdown: when to use it, what it needs, numbered Steps naming the tools to call, a decision table and the rules to keep. Follow the Steps in order.
skills.search
Find step-by-step instructions for a common job, written for you to follow with these tools: cutting the pauses, ums and restarts out of a talking video, for one. Search in the user's words; every skill comes back best first with its score (roughly 0 to 1). Below 0.1 is unrelated; a real fit usually scores 0.15 to 0.45, lower for a short or general ask, and an unrelated skill that shares words can score as high, so read the description of each one above 0.1 to judge the fit. Read one with skills.get, then follow its Steps.
adjustment
adjustment.add
An empty clip on a video track whose effects (filter.add with its clip_id) change everything below it while it runs: a colour grade or blur over a stretch of the edit. Returns the edit result (see the server instructions).
caption
caption.add
Captions on a video track from segments (with optional word timings for highlights), from SRT/VTT text, or in_clip: segments timed in seconds of a clip's media, such as transcript word times, placed where they play. One clip per caption; returns their clip_ids. A style field you leave out takes the published default (video://catalog/text: bold white Inter at 6% of the frame height, near the bottom, with a black outline); timeline.get shows the full style. Burned in when exported. Returns the edit result (see the server instructions).
cutout
create.cutout
A subject without its background, local: ProRes 4444 with alpha and the sound, or a PNG, to lay over a new background. subject any (BiRefNet) cuts out products, animals or objects; people (MODNet) is fast enough for long video. Long-running: a task, or {job_id, media_id} for job.get.
edit
edit.batch
Apply many edits as one change: one new timeline_id, one preview. All apply or none do. Use {"$ref":"ops[N].clip_id"} (or track_id, clip_ids[M]) to use an id an earlier op made. Returns the edit result plus results: [{tool, clip_id?, clip_ids?, track_id?}] per op.
judge
judge.ask
Ask TypeSafe Jev, a fast judgment model (preview), your questions about a state you give, and get typed answers back in about a second. Jev sees exactly the state: each entry under its name, and your questions refer to entries by name in backticks ("in `passage`"). An entry is text (a string, or a JSON object or array of related facts) or a picture: {media_id} for an imported image, {media_id, at_seconds} for the frame of a video at that time. Mix them freely. Each call stands alone, so put everything a judgment needs into its state. Choose the type by the answer you need. noul: yes or no, answered as noul, the probability of yes from 0 to 1 (0.5 or more reads as yes). choice: one of options you name, answered as choice plus probabilities and confidence. score: a degree on levels you order, answered as score (0 is the first level) plus confidence. box: where one thing is in a picture, answered as box {x, y, w, h} in fractions of that picture plus confidence. Write each question as one thing, worded so yes means it is there. Open with what the state is ("`passage` is a transcript of someone speaking off the cuff"), and give a noul criteria {true, false} with an example of each: Jev answers most accurately from examples. To locate, name the one thing so only it fits ("the yellow headline 'Get started' at the top of `shot`") and ask a noul whether it is there; trust a box with high confidence. One call answers many questions about one state at once, so judge many items together: put the shared text in state once, and give each item its own question carrying its own marked copy. Filler words: state {passage: "So basically the way this works is"}, and per word a noul "`passage` is a transcript of someone speaking off the cuff. With one word marked: "So [[basically]] the way this works is". Is the marked word filler, so the sentence says the same without it?" with criteria {true: "the [[the]] report is late", false: "the report is [[late]]"}. A shot: state {shot: {media_id, at_seconds: 12.5}}, choice "What fills `shot`?" with options {speaker: "A person talking to camera", screen: "A screen recording", none: "Anything else"}. Both: state {line: "Click Get started", screen: {media_id, at_seconds: 4}}, noul "Does `screen` show the button `line` talks about?". Up to 300 questions, 8 pictures and 200k characters of text a call. To find where something shows in a video or an edit, media.seek takes it in plain words; to measure every frame, media.analyze look asks your questions of frames it samples. Guide to writing questions: https://docs.typesafe.ai/primitives and https://docs.typesafe.ai/images.
lipsync
create.lipsync
Make a person on camera say different words: their mouth is redrawn to match the speech you give (a re-recorded line, a create.voiceover, a word taken from elsewhere in the take). Runs at the user's lip-sync provider on their own key (sync. labs), and the provider bills them for each second sent. To replace a line or swap a word, give range, the span of the video where it is said, and audio (with audio_range) holding just the new words. The result is that span alone, re-synced and carrying the new speech, as long as the speech with sync_mode remap; place it over the original span (clip.add on a track above, or clip.replace) and mute the old words. Send only the span: it costs less and finishes sooner. Lip sync is for when the face stays on screen while the words change. When the speaker is off screen at that moment, or a cutaway (b-roll, the screen being talked about, a reaction) can cover the splice, the cutaway hides the edit without it. Takes minutes. Long-running: a task, or {job_id, media_id} for job.get. The same recipe returns the same media. Provider limits (plan length, credits, file size) come back as limit_exceeded with the provider's error_code.
matte
create.matte
A solid or gradient picture (PNG, any length on a timeline): backgrounds, slugs, colour washes with clip.set_blend. Gradients work like CSS: angle 180 runs top to bottom; radial reaches the corners; colours may carry alpha (#RRGGBBAA). Long-running like every create.* tool, but quick.
motion
create.motion
Render animated HTML to a video with alpha, frame-exactly: lower thirds, animated titles, callouts, logo stings, kinetic type, generated graphics. Place the media_id with clip.add on a track above the video. Up to 60 s, and width × height × fps × seconds up to 30 s of 1080p30. Runs in the sandbox: no network (inline everything, load libraries from lib/; assets are for imported files the page must show as they are, like the user's logo or a font), fixed memory and time limits. To match a reference you were shown, rebuild it in HTML/SVG; it does not need importing. Long-running: returns a task, or {job_id, media_id} for job.get. The same recipe returns the same media.
qa
qa.check
Measure the rendered timeline: gaps in the picture, offline media, rendered against expected frame count, integrated loudness (LUFS) and true peak (dBTP), plus black and silent stretches when you give their settings. With speech {min_probability}, every cut is listed with speech facts: the speech probability of the mix just before and after it (Silero VAD), whether it lands while someone is speaking, the seconds without speech each side, and, per clip edge, the transcript word it cuts through and how much of that word is lost (from the media's transcript, when it has one). Facts only, no verdicts. Short timelines answer at once; longer ones return a task or job.
render
render.frames
Look at a timeline (or a media file): up to 16 frames as one contact-sheet image (layout grid) or one image each (single). Media frames are numbered at the media frame rate; a picture that can be see-through (alpha or a palette) is shown over a light checkerboard, so transparency shows as checks and a background baked into the file as itself. size full: up to 4 frames at the sequence (or media) size from the original media, for thumbnails and stills to keep. format webp (default), png or jpeg, with quality for webp and jpeg. Each image comes inline and with a signed download url.
stabilized
create.stabilized
A steadied copy of shaky video, local (vid.stab): one pass measures the camera shake over the whole media, a second moves each frame against a smoothed camera path. New media, ProRes with the sound, to put on the timeline in place of the shaky clip (clip.replace keeps its place and timing). Long-running: a task, or {job_id, media_id} for job.get.
stems
create.stems
The sound of a video or audio file pulled apart into stems, each new audio media for clip.add: vocals (voices, spoken or sung), drums, bass, other (everything else: guitars, keys, effects, room noise) and no_vocals (all but the voice, in one file). Laid together at the same time, the four stems make the original sound again. Use it to keep only the voice (lose the music under an interview: vocals), keep only the music (take the voice out of a clip: no_vocals), turn the music down under speech (vocals and no_vocals on their own tracks, with their own gain), or take a beat or a bass line on its own. Demucs v4 (htdemucs), local, on the CPU: about a fifth of the media's length on 8 cores (a minute of sound in about 15 s). Built for music; on speech with background noise, vocals keeps the voice and other takes most of the noise. Media up to 3 hours. Each stem is a 32-bit float WAV, 44.1 kHz stereo, as long as the original; the same media and stems give the same media again while they last. Long-running: a task, or a job_id for job.get.
still
create.still
Render an HTML page to a PNG: title and end cards, thumbnails, overlays, designed text. Transparent where nothing is painted. Capture waits for fonts, and for window.__ready if the page sets it to a promise (up to 10 s). Runs in the sandbox: no network (inline everything, load libraries from lib/; assets are for imported files the page must show as they are, like the user's logo or a font), fixed memory and time limits. To match a reference you were shown, rebuild it in HTML/SVG; it does not need importing. Long-running: returns a task, or {job_id, media_id} for job.get.
text
text.set
Change a title's or caption's text, or restyle many at once (clip_ids, or every one on track_id). The style is merged; null turns an outline, shadow, box or highlight off. Highlight modes and fonts: video://catalog/text and video://catalog/fonts. Returns the edit result (see the server instructions).
title
title.add
Text on a video track, over the tracks below: styled with font, size, colour, outline, shadow and box, placed by x/y, revealed with a typewriter or word animation. A style field you leave out takes the published default (video://catalog/text: bold white Inter at 9% of the frame height, centred, with a soft shadow); timeline.get shows the full style. It is a clip, so transforms, masks, animations and transitions apply. Returns the edit result (see the server instructions).
voiceover
create.voiceover
English text spoken by a natural voice (Kokoro, local; the model downloads once) as WAV media. words (default) times each word into the media transcript (media.get include transcript). Long-running: a task, or {job_id, media_id} for job.get.

Endpoints

URLTransportStateLatencyChecked
https://api.cuttingfloor.ai/mcp streamable-http answering 357 ms 2 min ago

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67 tools answering

cuttingfloor — questions

Answers built from our own checks of this server.

What can cuttingfloor do?
It exposes 71 tools, read directly from the server on our last check. Among them: adjustment.add, audio.fade, audio.set_gain, audio.set_master, audio.set_pan, caption.add and 65 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
What is cuttingfloor mostly used for?
Its tools cluster around clip, media and timeline. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.
Is cuttingfloor working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 92 of 92 checks got a reply (100.0%), average response time 480 ms. The bar chart above shows every period we have measured.
How do I connect cuttingfloor?
Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does cuttingfloor need an API key?
No. cuttingfloor completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 71 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is cuttingfloor?
It answers our handshake in 480 ms on average, which is faster than 28% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.
Is cuttingfloor open source?
We cannot say either way: written in TypeScript and 0 stars on GitHub, but we could not determine the licence, and without one the code is not open source by default.