MIT-licensed tool lets LLMs truly analyze video by converting it to frames and transcripts

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A developer has released an open-source tool called claude-real-video that addresses a core limitation of large language models, which cannot natively process video despite being marketed as multimodal. The tool uses ffmpeg to extract scene-aware frames and Whisper to generate timestamped transcripts, merging both into a single timeline file that any LLM can read. A --text-anchors flag ensures on-screen text is never missed between sampled frames, while an --adaptive flag handles slow visual deformations. The tool runs entirely on the user's machine with no third-party API involvement, and processes a 90-second video in roughly one to two minutes on an M-series Mac. Released under the MIT license on GitHub, the project has accumulated over 1,700 stars and approximately 8,000 installs in the past month.

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