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Fetch multi-platform video metadata, transcripts, insights, and frames for analysis.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "framefetch" yet — see the docs or source repo.
Use framefetch to fetch this TikTok video's metadata, Whisper transcript, engagement insights, and one frame every 5 seconds, then organize everything into structured JSON.
A structured result containing video details, transcript text, engagement metrics, and timestamped frame image links.
Use framefetch to retrieve this YouTube video's title, description, transcript, and parametric key frames, then break the content into topic-based section summaries.
Video metadata, section-by-section summaries, and key frame references mapped to each segment.
Using framefetch, batch fetch metadata, transcripts, and insight metrics for this list of Instagram and Pinterest video URLs, then generate a comparison table.
A comparison-ready summary table showing each video's themes, performance, and content differences.
Extract video frames and metadata for LLM-powered video analysis workflows.
Fetch YouTube transcripts and metadata with multi-backend audio transcription.
Enable AI agents to search YouTube and access metadata, comments, and transcripts.
Extract YouTube transcripts, timestamps, metadata, and export them as files.
Extract YouTube transcripts and metadata as Markdown for fast AI summarization.
Analyze videos with frame extraction, scene detection, and metadata retrieval.