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Process videos with natural-language transcription, clipping, and file management.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Video Tools MCP" yet — see the docs or source repo.
Please transcribe this meeting video into text and organize the transcript in chronological paragraphs.
A transcript of the video, suitable for reviewing meeting content or further editing.
Please cut the segment from 2:10 to 3:05 from this video and save it as a new file.
A new video file containing the requested time range.
Please list the files generated by the current video processing workflow and organize the transcript and clipped video separately.
A file listing plus the requested file management actions.
Content creators, researchers, or office workers can use natural language to transcribe videos into readable text. This reduces manual listening time and makes it easier to extract and reuse content.
When a user only needs part of a video, they can describe the start and end times in natural language to cut a clip. This is useful for extracting demos, interview highlights, or key moments from longer videos.
After transcription and clipping, users can also handle related file management tasks. This helps organize outputs more efficiently and reduces manual searching and filing.
This is an MCP server for video processing through natural language. Based on the provided information, it supports transcription with Whisper, segment cutting with FFmpeg, and file management.
The provided information explicitly mentions three capabilities: video transcription, segment cutting, and file management. No additional advanced editing features are described.
The current materials do not provide installation steps or prerequisite details. Since the description mentions Whisper and FFmpeg, please check the source repository for exact environment setup requirements.
Edit, merge, overlay, and convert videos through ffmpeg-powered MCP tools.
Edit, subtitle, and transcode videos through AI-driven FFmpeg workflows.
Analyze videos with frame extraction, scene detection, and metadata retrieval.
Use natural language to process, analyze, and stream audio and video.
Analyze videos from 1000+ platforms with transcription, frame insights, and metadata extraction.
Extract video frames and metadata for LLM-powered video analysis workflows.