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AI Video2Knowledge: Transform Videos into Structured Insights

AI Video2Knowledge: Transform Videos into Structured Insights

Regular price £28.99
Regular price £28.99 Sale price
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Works withClaude CodeCursorCodexGemini CLI
AI Video2Knowledge: Transform Videos into Structured Insights

AI Video2Knowledge: Transform Videos into Structured Insights

Regular price £28.99
Regular price £28.99 Sale price
SAVE Sold out

AI Video2Knowledge: Transform Videos into Structured Insights

AI Video2Knowledge is an AI agent skill designed to convert videos into structured insights by generating timestamped subtitles and knowledge artifacts. It provides a seamless method to derive value from video content through a local processing setup, ensuring privacy and data security by keeping all inputs and outputs on the host machine.

What this skill does

  • Converts videos into timestamped captions using a native multimodal visual language model (VLM) or through audio analysis with ASR transcription.
  • Supports transcription for both English (faster-whisper) and Mandarin (FunASR Paraformer), including pinyin repair for enhanced accuracy.
  • Refines the extracted information into various formats: structured knowledge documents, self-contained HTML pages, deduplicated CSV files, Anki apkg decks, and illustrated notes.
  • Operates entirely locally by default, ensuring that video, audio, and output data remain secure on the host device without being uploaded to external servers.
  • Offers optional cloud integration for transcription and processing through opt-in configurations.

Who it is for

This skill is ideal for developers and teams using AI coding agents such as Claude Code, Cursor, and Codex who need to transcribe and summarize video content effectively. It supports workflow integration for individuals focusing on content analysis, education, and documentation.

Use cases

  • Transcribing educational seminars or lectures to create learning materials such as Anki decks for revision.
  • Summarizing video meetings or presentations into concise, accessible format documents.
  • Converting video tutorials into structured knowledge bases with various accessible outputs for wider distribution.

Technical details

  • Utilizes native multimodal VLM for reading video frames and ASR models like faster-whisper for English and FunASR Paraformer for Mandarin transcription.
  • Produces output formats like CSV, HTML, Anki decks, and illustrated notes with fully local data processing.
  • Supports optional cloud-based endpoints for those opting in, labeled explicitly for third-party uploading.

Source & Licence

This package is built on open-source work published by CacinieP (CacinieP/video2knowledge) and distributed under MIT. The original licence text and copyright notice are included in your download.

Personal and commercial use, modification and redistribution are permitted, provided the original copyright and licence notice are retained.

Your purchase covers curation, licence verification, packaging, documentation and instant delivery. It does not grant exclusive rights to the underlying open-source code, which remains available under its original licence.

Delivery & Support

  • Delivery: instant — a secure download link is emailed to you as soon as payment is confirmed.
  • Format: ZIP archive containing the skill files, documentation and the original licence.
  • Support: support@mcpcart.com — we aim to reply within 2 business days.
  • Updates: updates are included only where stated on this page.

Refunds

This is a digital product delivered immediately after purchase. By completing your order you request immediate delivery and acknowledge that, once the download has been accessed, the statutory right to cancel no longer applies to the extent permitted by law. Refund requests are handled in accordance with our published Refund Policy.

Claude, Codex, Gemini and Cursor are trademarks of their respective owners. MCP Cart is an independent marketplace and is not affiliated with, endorsed by, or sponsored by any of them. Compatibility references describe interoperability only.

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