mcp-video-frames
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Alternatives to mcp-video-frames
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Related Servers
- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to watch YouTube videos by extracting frames at scene changes and visual references, pairing each frame with the exact words spoken at that timestamp. Provides dense frame-transcript interleaving for any model.31 npm5MIT
- FlicenseNot gradedqualityBmaintenanceEnables AI clients to watch and hear videos from local files or YouTube, Vimeo, and Loom links by returning timestamped key frames, a transcript, a contact sheet, and a combined timeline, with all processing done locally.-
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to read videos from YouTube links, web pages, media URLs, or local files by returning timestamped transcripts, labelled frame contact sheets, and lossless audio or spectrograms. Also searches YouTube, channels, pages, and folders to find videos worth reading.MIT
- AlicenseAqualityCmaintenanceLets AI agents inspect local or remote videos by reading metadata, detecting shots and cuts, extracting frames as images, and checking keyframes for seeking and streaming, all via local FFmpeg without an API key.51MIT
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to download, convert, and visually analyze videos by providing timestamped frames and locally transcribed speech, all without API keys.MIT
- AlicenseNot gradedqualityCmaintenanceEnables Claude to analyze videos by combining local ffmpeg/OpenCV measurements (exact cut timings, frame extraction, second-by-second camera motion, flashes and audio hits) with Gemini's reading of video in motion and audio. Users can break down reference videos shot by shot, compare a reference against their own edit for concrete fixes, and inspect any video segment before publishing.1MIT
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one extracts frames from videos, the other retrieves metadata. No overlap in functionality; each addresses a separate need.
Both names follow a verb_noun pattern: 'view_frames' and 'video_info'. The verbs differ ('view' vs 'video') but the structure is consistent. Minor deviation in verb choice, but pattern is clear.
With only 2 tools, the set is minimal but each tool is substantial and well-scoped, covering the core functions of frame extraction and metadata retrieval. Slightly thin for a full video analysis workflow, but reasonable for a focused server.
The set covers the primary operations (extract frames, get info) but lacks additional common video operations such as transcoding, clipping, or audio extraction. The domain is video analysis, and while the two tools address key needs, there are notable gaps that agents might encounter.