eclat-remotion
Click 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., "@eclat-remotionlist available templates"
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.
Instavar Remotion Templates
Open-source, agent-friendly Remotion templates for turning a brief into a validated local video. The creative work happens in your Codex or Claude Code conversation. The Instavar MCP server supplies public template contracts, examples, and troubleshooting without requiring an Instavar account or API key.
If your browser blocks the app link, run:
git clone https://github.com/instavar/remotion-templates.git
cd remotion-templates
npm install
codex mcp add instavar-remotion --url https://instavar.com/api/mcp/templates
codexThen ask Codex to read AGENTS.md and make a video.
Claude Code
git clone https://github.com/instavar/remotion-templates.git
cd remotion-templates
npm install
claude mcp add --transport http instavar-remotion https://instavar.com/api/mcp/templates
claudeThe repository also includes the same server in .mcp.json, so Claude Code can
offer to enable it when the project is trusted. Then ask Claude Code to read
CLAUDE.md and make a video. A direct custom connector does not require
publication in Anthropic's connector directory.
Related MCP server: SudoMock
Manual workflow
npm run video:validate -- examples/proof-walkthrough.video.json
npm run video:preview -- examples/proof-walkthrough.video.json
npm run video:render -- examples/proof-walkthrough.video.jsonRendered videos go to out/ by default.
video:preview renders one midpoint frame for every scene into
out/previews/<video-id>/. This makes visual review possible in headless agent
environments. Add --studio to open Remotion Studio instead.
Create a starter spec:
npm run video:scaffold -- proof-walkthrough "Why this equation works"Audio without an API key
Audio intent is explicit. Set audio.mode to narration, music, or silent.
Do not rely on the presence of an MP4 audio stream because a stream can contain
only silence.
To generate narration with the operating system voice on macOS or Linux:
# First add the approved script to audio.narrationText.
npm run video:narrate -- my-video.video.jsonThe command writes a local WAV under public/generated/, updates
audio.narrationSrc, and scales automatic scene timings to the measured
narration duration. The generated directory is ignored by Git.
For private Supertonic narration with exact scene boundaries, open
https://instavar.com/voice and write one paragraph per scene. Download the
WAV and timing manifest, place the WAV under public/generated/, then run:
npm run video:timing -- my-video.video.json \
--audio public/generated/narration.wav \
--manifest ~/Downloads/instavar-supertonic-f1.timing.jsonThe command maps narration beats to scenes in order, rejects a beat-count mismatch, records the measured timing in VideoSpec, and updates automatic scene durations. The script and generation stay on the user's device. No API key, hosted aligner, upload, or account is required. This provides scene-level sync, not word-level caption timing.
To use another local engine, set a command array without invoking a shell. The placeholders are replaced before the process starts:
export INSTAVAR_TTS_COMMAND_JSON='["/absolute/path/to/tts-wrapper","--text","{text}","--output","{output}"]'
npm run video:narrate -- my-video.video.json --provider customThis adapter can wrap Supertonic, Kokoro, Audio8, NeuTTS, or another local engine. Keep model weights and virtual environments outside this repository.
The default recommendation is deliberately small:
Use the operating system voice for the fastest zero-download trial.
Use Supertonic when a compact CPU-first model matters. Our bounded local test measured about 562 MB peak resident memory.
Consider Kokoro when its voice set fits the brief. Our bounded local test measured about 1.69 GB peak resident memory.
Treat Audio8 as an optional quality experiment, not the default download. Its checkpoint is about 2.4 GB, and short M2 runs used roughly 5.5 to 7 GB.
Treat NeuTTS as a legacy advanced adapter. Our prior environment and model footprint was roughly 11 GB and required Python, model, codec, phonemizer, and reference-voice setup.
These measurements come from different prompts and runtimes. They establish local feasibility, not a quality ranking.
After rendering, audio QA runs automatically. If the spec expects audio, the command fails when no audio stream exists or the measured peak is at or below -60 dB. Run the same check independently with:
npm run video:qa -- my-video.video.json out/my-video.mp4Templates
qa-ad: hook, source-video placeholder, explanation, and call to actionproof-walkthrough: equations, worked reasoning, and takeawayannouncement-brief: headline, supporting points, and next actionsocial-remix: caption-forward framing for an existing clipfinance-brief: comparisons, numeric highlights, caveats, and recommendation
All five support 9:16, 4:5, and 1:1 output. The renderer now uses
scene-specific editorial layouts instead of printing internal scene identifiers
above a generic text block. announcement-brief supports hero, statement,
mechanism, outcome, and guidance scenes with light, dark, and clinical palettes.
The visual safeguards are defaults, not prompt suggestions:
internal scene kinds stay hidden
decorative eyebrow labels are omitted unless explicitly authored
all-caps and implementation labels produce diagnostics
long headlines and dense point lists produce diagnostics
four-scene videos with weak layout variety produce diagnostics
Fraunces carries display hierarchy and Inter carries body copy
every scene receives a preview frame before the final render
expected audio is checked for audible signal after rendering
Privacy and keys
No Instavar account or API key is needed. The public MCP tools are read-only and deterministic. Your brief and local assets remain in your own agent conversation and workspace. Rendering runs on your machine.
An Instavar API key unlocks the hosted Studio workflow, including managed rendering, storage, review, publishing, and metrics through @instavar/mcp-server. The free local path remains available without a key.
Licensing
Instavar-authored code in this repository is MIT licensed. Remotion has its own license and terms. Review the current Remotion license for your use case. See TRADEMARKS.md before using Instavar names or marks.
Contributing and security
See CONTRIBUTING.md, CODE_OF_CONDUCT.md, and SECURITY.md.
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