squish
OfficialClick on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@squishcreate a contact sheet from meeting-recording.mp4"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
@getsquish/squish

Give AI random access to video. Instead of forcing a model to watch a clip from beginning to end, Squish converts continuous video into an addressable visual representation — one an agent can navigate, revisit, and progressively refine. Timestamped contact sheets are the first implementation of that primitive: a grid of frames, each cell stamped with its absolute timecode. Everything runs on your machine. From the makers of getsquish.app.
Agents don't consume videos — they navigate them. Real run: a scene cut pinned to 0.2 s by retrieving 34 frames — not 3,088 (overview → zoom → zoom).
The demo is the primitive. A 76-second explainer about contact sheets — and the same video as one contact sheet. One needs a play button; the other you just read:
Why this works
Video is continuous; reasoning is sparse. Most questions touch a tiny fraction of the timeline. Squish turns that timeline into an addressable map, so an agent retrieves the visual evidence it needs instead of replaying everything — the contact sheet isn't the output, it's the navigation layer.
Related MCP server: videoseek-mcp
Install
npm install -g @getsquish/squish # or one-shot: npx -y @getsquish/squish <video>Requirements: Node ≥ 20 · ffmpeg + ffprobe on PATH
(macOS brew install ffmpeg · Ubuntu sudo apt-get install ffmpeg).
CLI
squish clip.mov # sheets land beside the input
squish clip.mov --density 5x5 --json # denser grid + machine-readable output
squish clip.mov --start 1:00 --end 1:30 --density 5x5 # zoom into a rangeOutput: <basename>.sheet-N.jpg — a timecoded frame grid. Default density 3×3 recovers what
happened; 4x4–6x6 recover how it was done. --out <dir> picks the destination.
--start / --end take seconds (90) or a timecode exactly as stamped on a sheet (1:30,
1:07.3) and window the run to that range. Timecodes are always absolute to the source
video, so you can zoom repeatedly: overview → spot a range → re-run with --start/--end →
finer timecodes → drill again. Short windows stamp sub-second timecodes (1:07.3) so adjacent
cells stay distinguishable.
With --json, stdout is one object (frozen contract — parse contract to detect breaking
changes):
{
"input": "/abs/path/clip.mov",
"duration": 20.275,
"frames": 9,
"sheets": 1,
"files": ["/abs/path/clip.sheet-1.jpg"],
"warnings": [],
"contract": "squish-cli-v0"
}Exit 0 success · 1 failure (message on stderr). Temp frames are always cleaned up.
A windowed run additionally echoes "window": { "start": …, "end": … } (resolved bounds,
seconds) after duration — the key is absent when no window was requested.
MCP server
squish mcp # stdio serverOne tool, squish_video — { video_path, density?, start?, end?, out_dir? } → the CLI
contract plus timecodes[][] (one per frame, per sheet; m:ss, sub-second m:ss.d when
a window is short), stamped "contract": "squish-mcp-v0". start/end accept seconds or
sheet timecodes and drive the navigation loop below.
Works with Claude Code, Claude Desktop, Cursor, Hermes, and any stdio MCP client:
{
"mcpServers": {
"squish": { "command": "npx", "args": ["-y", "@getsquish/squish", "mcp"] }
}
}The navigation loop
Overview — call
squish_video(MCP) orsquish clip.mov --json(CLI) and read the sheet(s) with vision. Cells run in time order, left→right, top→bottom.Navigate — spot the regions that matter; every cell carries an absolute timecode.
Zoom — call again with
start/endset to the timecodes you spotted, only where uncertainty remains: denser sheets of a narrower window, addresses still absolute.Repeat until the answer is observable — never re-read the whole clip at high density when one range matters.
Cite absolute timestamps ("at 0:07 the press comes down").
Privacy
The CLI and MCP server process everything on your machine — nothing is uploaded, ever, and every density is free. Want remote processing instead (CI, serverless, no ffmpeg)? There's a hosted API — an intentional upload, prepaid credits, with a free daily allowance for accounts that never purchased.
This repository
This is the engine — the CLI + MCP mouths of Squish, published to npm as
@getsquish/squish. It is a curated,
mirror-first export of a private monorepo (which stays the source of truth); history here
starts at the first public release. See CONTRIBUTING.md for how changes
flow.
Not in this repo, on purpose:
the getsquish.app web app (PWA) — same core planners, browser hands;
the hosted API (
api.getsquish.app) — the paid rail: intentional upload, prepaid credits, a free daily allowance for never-paid accounts;brand assets — the Squish name, logo, mascot, and OG images are reserved.
src/ CLI (main/args) · engine (probe → plan → extract → compose → write) · MCP server · sheet renderer
src/core/ pure planners shared with the web app: density · sampling · grid layout · timecode format
tests/ node:test suite + a real-MCP-client e2e
SKILL.md drop-in agent skill teaching the contact-sheet + zoom-loop recipeLicense
Apache-2.0 (with NOTICE). The Squish name, logo, mascot, and getsquish.app brand assets are not licensed by this repository.
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