Show HN: Turn narrated screen recordings into data for AI agents (local, MIT) (github.com)

A new tool called "talkthrough-mcp" has been introduced, allowing users to convert narrated screen recordings into structured data for AI agents, effectively automating feedback ingestion. This local-first server processes video and audio files to produce timestamped transcripts, speaker labels, scene-change keyframes, and OCR'd on-screen text, all while ensuring a lightweight model context with lazy retrieval tools. Notably, there’s no reliance on cloud services or large language models (LLMs); everything operates on the user's machine using tools like ffmpeg and whisper, enhancing privacy and efficiency. This development holds significant implications for the AI/ML community as it streamlines workflows around software development and project management. By transforming verbal narration into actionable insights, it facilitates processes like bug filing, specification writing, and backlog building. The ability to anchor timestamped remarks to real logs in software systems makes it easier to trace actions and decisions. The tool also locally implements speaker diarization, allowing for enhanced meeting transcriptions with speaker identification, all without compromising user data security. This innovative approach not only democratizes access to AI-assisted task automation but also positions local processing as a viable alternative to cloud-based solutions.