FrameFetch MCP Server
One social-video URL in → metadata, transcript (captions or Whisper), engagement insights, and parametric frames out. 6 platforms (YouTube, Shorts, TikTok, Instagram, Pinterest, Reddit). REST + MCP. Pay per call with x402 (USDC), no account.
Documentation
FrameFetch
Any social-video URL → metadata, transcript, insights & frames.
Agent-first video data API + MCP server. Pay per call, or with x402 (USDC) — no account.
FrameFetch turns one YouTube, YouTube Shorts, TikTok, Instagram Reels, Pinterest, or Reddit video URL into a single JSON response: metadata, engagement insights, a transcript (captions or Whisper), and parametrically-sampled frames (every Nth / 1-per-second / a time range, at any width). Built API-first and MCP-first for AI agents.
This repo is the open-source client + docs. The service itself runs at framefetch.net — you bring a free API key (or pay per call with x402); the backend stays hosted.
Why
An LLM can't watch a video. To reason about one it needs the video turned into text and images first — a transcript, metadata, and a few frames. FrameFetch returns all three from a URL, across six platforms, through one schema.
Install
npm install framefetch
Node 18+ (uses built-in fetch). Get a free key: framefetch.net.
Quick start
import { FrameFetch } from 'framefetch';
const ff = new FrameFetch({ apiKey: process.env.FRAMEFETCH_API_KEY });
const r = await ff.extract({
url: 'https://www.youtube.com/watch?v=jNQXAC9IVRw',
fields: ['metadata', 'transcript', 'frames'],
frames: { mode: 'fps', fps: 1, width: 480 },
});
console.log(r.metadata.title); // "Me at the zoo"
console.log(r.transcript.text); // "Alright, so here we are…"
console.log(r.frames.count); // 19
Scoped helpers
await ff.metadata(url); // title, author, duration, views, likes…
await ff.transcript(url); // captions, else Whisper
await ff.frames(url, { mode: 'fps', fps: 1, width: 512 });
await ff.platforms(); // capability matrix (no key)
await ff.status(); // live service health (no key)
No signup
const ff = new FrameFetch(); // no key
await ff.demo('https://youtu.be/jNQXAC9IVRw'); // instant metadata, rate-limited
const { key } = await ff.createKey('[email protected]'); // self-serve key + free credit
Use it from an MCP agent
FrameFetch ships an MCP server (Streamable HTTP) with the tools framefetch_extract and framefetch_platform_capabilities. Add it to Claude, Cursor, or any MCP client:
{
"mcpServers": {
"framefetch": {
"url": "https://framefetch.net/mcp",
"headers": { "Authorization": "<YOUR_FRAMEFETCH_KEY>" }
}
}
}
Or one line:
claude mcp add --transport http framefetch https://framefetch.net/mcp \
--header "Authorization: <YOUR_FRAMEFETCH_KEY>"
Pay without an account (x402)
Autonomous agents can pay per call in USDC via x402 on Base — no signup, no human in the loop. Discoverable in the x402 Bazaar and at /.well-known/x402.json. Humans can use a free tier, prepaid credits, or a Stripe card.
Errors
import { FrameFetchError } from 'framefetch';
try {
await ff.transcript(url);
} catch (e) {
if (e instanceof FrameFetchError && e.status === 402) {
// out of credit — top up at framefetch.net or via x402
}
}
API surface
| Method | Endpoint | Auth |
|---|---|---|
extract({ url, fields, frames }) | POST /v1/extract | key |
metadata(url) | POST /v1/metadata | key |
transcript(url) | POST /v1/transcript | key |
frames(url, spec) | POST /v1/frames | key |
platforms() | GET /v1/platforms | — |
status() | GET /v1/status | — |
demo(url) | POST /v1/demo | — |
createKey(email) | POST /v1/keys | — |
Full OpenAPI: framefetch.net/openapi.json · Docs: framefetch.net/docs
Links
Website · Docs · Pricing · Status · Guide: giving an agent video data
License
MIT