Catch bad animations before they ship. Deterministic motion audit + vision-LLM design review.
Catch bad animations before they ship. Deterministic motion audit + vision-LLM design review. The motionlint mcp server wraps that behind the Model Context Protocol, so an assistant can use it rather than through you.
Deterministic — measured from the live page, no LLM involved. One-time prerequisite: npx playwright install chromium.
motionlint on npm is all you need. Most clients run it directly, so configuration is a few lines and a restart.
You will need 3 environment variables: ANTHROPIC_API_KEY, OPENAI_API_KEY, GOOGLE_API_KEY. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
This sits in the AI and media services group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. It is maintained by bobaba99; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
{
"mcpServers": {
"motionlint": {
"command": "npx",
"args": ["-y", "motionlint"],
"env": {
"ANTHROPIC_API_KEY": "your-value",
"OPENAI_API_KEY": "your-value",
"GOOGLE_API_KEY": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| ANTHROPIC_API_KEY | Credential the server authenticates with. | Yes |
| OPENAI_API_KEY | Credential the server authenticates with. | Yes |
| GOOGLE_API_KEY | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.