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  3. Envie
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Envie

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
View RepositoryVisit Website

Your AI writes HTML; Envie renders it to video on your machine, verifies it and shows it back.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

One-click editor setup isn’t available for this listing yet β€” we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ
No confirmed setup config for this listing yet. We only publish a config block when the install details come from the project itself β€” its README, its docs, or a verified owner. We haven’t found those for Envie, and we’d rather show nothing than a guess you’d paste into your client. Follow the project’s own setup instructions for the current steps.
Install Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Documentation Overview

Envie

AI video, verified.

Describe a video to your AI. Get a real file back.

Envie gives Claude Code and any MCP client a deterministic render engine: headless Chrome filmed frame by frame, six verification gates, and a full read-back layer. Free. No watermark. No account.

By GOL Productions.


The Problem

AI can write code. AI can describe video. But AI can't see what it madeβ€”so it guesses, you render, it's wrong, you describe what's wrong, repeat.

The Solution

Code
You: "Make me a 15-second launch video for my app"
AI:  [writes HTML composition]
AI:  [calls envie_render]
AI:  [calls envie_see to check frames]
AI:  "Done. Video at output.mp4. All 6 gates passed."

Envie renders what your AI writes, verifies it machine-checks, and lets your AI see the result. No guessing.


Install

Terminal
npx @golproductions/envie@latest setup

Detects Claude Code, Cursor, Windsurfβ€”registers with all of them. Then just ask:

"Make me a 15-second vertical launch video for my app"

Manual install
config.json
{ "mcpServers": { "envie": { "command": "npx", "args": ["-y", "@golproductions/envie", "mcp"] } } }

Or for Claude Code:

Terminal
claude mcp add --scope user envie -- npx -y @golproductions/envie mcp

How It Works

Code
β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”     β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”     β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”     β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚   WRITE     β”‚ ──► β”‚   RENDER    β”‚ ──► β”‚   VERIFY    β”‚ ──► β”‚    SEE      β”‚
β”‚             β”‚     β”‚             β”‚     β”‚             β”‚     β”‚             β”‚
β”‚ AI writes   β”‚     β”‚ Chrome filmsβ”‚     β”‚ 6 gates     β”‚     β”‚ AI checks   β”‚
β”‚ HTML comp   β”‚     β”‚ frame by    β”‚     β”‚ machine-    β”‚     β”‚ frames at   β”‚
β”‚             β”‚     β”‚ frame       β”‚     β”‚ check video β”‚     β”‚ timestamps  β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜     β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜     β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜     β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

1. Write

Your AI reads envie_guide and writes a composition: one self-contained HTML file with CSS animations, WebGL, Canvas, GIFsβ€”whatever the browser can render.

2. Render

envie_render films it deterministically. Headless Chrome with a virtualized clock: performance.now(), Date.now(), requestAnimationFrame, setTimeoutβ€”all seeked frame by frame.

Same composition = same video. Every time.

3. Verify

Six gates machine-check the result before delivery:

GateWhat it checks
G1File exists, valid container, β‰₯2.9s duration
G2Has both video and audio streams
G3Audio isn't silent (mean > -50dB)
G4No black segment > 2 seconds
G5No freeze > 8 seconds, < 60% total still time
G6Final 15% isn't dead (frozen or black)

A failing video comes back marked FAILED, with the gate report and an instruction not to deliver it, so your AI fixes the composition and renders again.

4. See

envie_see returns frames at chosen timestamps so your AI can judge layout and pacingβ€”not just whether the file exists.

5. Translate

envie_translate reads the finished file as data: per-frame motion, every cut and fade, still holds, LUFS, true peak, and how each audio hit sits against the nearest picture event.


Requirements

RequirementNotes
Node 24+Or later
ChromeOr set ENVIE_CHROME to your binary
ffmpeg + ffprobeMust be on PATH
AudioRequired. Videos with no audio fail G2 and G3

Audio options

OptionPlatformDescription
--narration "text"Windows onlyLocal TTS voiceover (SAPI)
--audio file.wavAll platformsOverlay any wav/mp3/m4a

Runs entirely on your machine. Nothing reaches GOL servers.


Formats

FlagContainerCodec
--format h264.mp4libx264 (default)
--format h265.mp4libx265 10-bit
--format prores.movProRes 422 HQ 10-bit
--format prores4444.movProRes 4444 10-bit
--format dnxhr.movDNxHR HQ

CLI

Terminal
npx @golproductions/envie@latest setup                   # register MCP server
npx @golproductions/envie@latest uninstall               # remove everything Envie added
envie render <comp.html> -o out.mp4 [options]            # render video
envie see    <comp.html|video.mp4> [--at 1000,4000]      # extract frames
envie verify <video.mp4>                                 # run gates
envie translate <video.mp4>                              # analyze motion/audio
envie guide                                              # print authoring guide
envie mcp                                                # start MCP server

envie here means npx @golproductions/envie@latest. Use @latest: plain npx runs an older globally installed copy if one exists.

Render options

Code
--narration "text"     # TTS voiceover (Windows)
--audio file.wav       # Overlay audio file
--fps 24               # Frame rate (default: 24)
--format h264          # Output codec
-o output.mp4          # Output path

Composition Format

One self-contained HTML file:

html
<!DOCTYPE html>
<html>
<head>
<style>
  body { margin: 0; width: 1080px; height: 1920px; overflow: hidden; }
  /* your animations */
</style>
</head>
<body data-duration-ms="15000" data-width="1080" data-height="1920">
  <!-- your content -->
</body>
</html>

Required attributes

AttributeDescription
data-duration-msVideo length in milliseconds (3000–300000)
data-widthCanvas width (default: 1920)
data-heightCanvas height (default: 1080)

What's virtualized

Everything the browser can animate:

  • CSS animations, transitions
  • Web Animations API
  • requestAnimationFrame
  • setTimeout, setInterval
  • Canvas 2D, WebGL
  • performance.now(), Date.now(), new Date()
  • Animated images (GIF, WebP, APNG, AVIF)
  • Math.random(), crypto.getRandomValues (seeded)
  • Classic Web Workers (run on the virtual clock)

NOT virtualized (avoid):

  • Module Web Workers and strict-mode worker code
  • WebAudio-driven visuals

Intent Assertions

Declare what the composition must achieve:

html
<body data-duration-ms="12000"
      data-expect-sync-ms="120"
      data-expect-no-holds-longer-than="3">
AssertionMeaning
data-expect-sync-ms="120"Audio hits must land within 120ms of a picture event
data-expect-no-holds-longer-than="3"No still hold may exceed 3 seconds

Failures are reported test-style:

Code
SYNC FAIL: mean audio-to-picture offset 380ms exceeds tolerance 120ms
HOLD FAIL: 2 hold(s) exceed 3s: 4.20s @0.40s, 3.10s @7.80s

Deterministic Rendering

The render engine virtualizes time itself:

javascript
// Inside the page during render:
performance.now()  // β†’ virtual clock
Date.now()         // β†’ virtual clock
new Date()         // β†’ virtual clock
Math.random()      // β†’ seeded PRNG

// Same seed, same composition = identical output

This is how the same HTML produces the same video, every render.

What "deterministic" means

Same machine + same Chrome version + same composition = bit-identical output.

Cross-environment, you may see variation from:

  • Font rendering (anti-aliasing, hinting differ by OS/GPU)
  • WebGL/Canvas floating-point precision
  • Chrome version changes
  • System font fallbacks (embed fonts to avoid)

The guarantee is reproducibility on your machine, not cross-platform bit-identity. That's the right scope: your AI iterates locally, re-renders, gets the same result.


Your Work Is Yours

GOL claims no ownership over your compositions or videos. Envie runs on your machine. Nothing you make reaches us.


License

Free to use, personal or commercial, under the GOL Free License. Envie is built by GOL Productions: you may use it and share unmodified copies with the credit, but not publish changed versions, build your own product from it, or sell it. What you make with it is yours. See LICENSE.


GOL Productions

Envie is part of the GOL Productions toolchain.

  • Check β€” Anti-hallucination layer for Claude Code
  • Exnos β€” Live browser verification

Product page Β· GitHub

Read the full README β†’View source on GitHub β†’

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Reviews

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Frequently Asked Questions about Envie

We don't have a confirmed install command for Envie yet, so we don't publish a generated one β€” a guessed package name would point at the wrong package or none at all. Follow the project's own README or setup instructions (https://github.com/golproductions/envie) for the current steps.

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
More technical detailsExpand β–Ύ
Last updatedSep 28, 2026
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27Quality signal: Emerging Β· 27/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20
Documentation & tools11/30
Adoption & activity1/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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