io.github.MarvinRey7879/framefetch

Extract structured data from ONE public social-video URL (YouTube incl. Shorts, TikTok, Instagram Reels, Pinterest, Reddit). Purpose: turn a video link into metadata (title, author, duration, date), insights (views/likes/comments), a transcript (captions, or Whisper when there are none — works on TikTok/Reddit too), parametrically-sampled video frames, and/or the on-screen text burned into those frames (OCR — captions, price tags, signage, lower-thirds). When to use: you have a video URL and need its text, stats, frames, or on-screen text for analysis, summarization, or grounding a model. When NOT to use: non-video pages, private/login-walled content, or bulk crawling (one URL per call). Returns: one JSON object containing only the requested fields plus a `cost` block (micro-USD). Frames come back as time-limited signed image URLs; text_overlay returns one entry per frame with the OCR text, per-line confidence, and bounding boxes. Cost/latency: metadata is sub-cent and fast; transcript is billed per audio-minute, frames per frame, and text_overlay per frame on top of that (all three also incur bandwidth for frames) — request only the fields you need and downscale frames via `width` to control cost. Billing: a free tier covers light use; agents can also pay per call with x402 (USDC) with no account. Example: { "url": "https://www.youtube.com/watch?v=...", "fields": ["metadata","transcript"], "frames": { "mode": "fps", "fps": 1, "width": 480 } }

Return a JSON matrix of which data types (metadata, insights, transcript, frames) each supported platform provides — YouTube, YouTube Shorts, TikTok, Instagram Reels, Pinterest, Reddit. Purpose: check what is available for a platform BEFORE calling framefetch_extract, so you only request supported fields. No input required.