A
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qualityD
maintenanceA MCP server for video multimodal understanding based on Alibaba Cloud DashScope, enabling video content analysis, summarization, scene recognition, and custom analysis.
2
MIT
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"A tool for video analysis" matching MCP servers:
- AlicenseAqualityAmaintenanceMCP server for video analysis — extracts transcripts, key frames with OCR, and annotated timelines from video URLs. Supports Loom and direct video files (.mp4, .webm). Zero auth required.581,10642MIT
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- FlicenseAqualityDmaintenanceAn MCP server that transforms LLM-enabled IDEs into professional video editors by pre-processing footage into text proxies, generating motion graphics via HTML/CSS, and orchestrating complex FFmpeg renders.4
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- AlicenseAqualityAmaintenanceProvides vision capabilities to Reasonix, enabling analysis of images/videos, OCR, and comparisons via OpenAI-compatible vision models.46MIT
- AlicenseAqualityCmaintenanceEnables AI clients like Codex, Claude Code, and Kimi Code to analyze public video URLs by downloading media, uploading it to Gemini, and returning timestamped production breakdowns covering shots, visual design, animation, motion, narration, music, sound effects, and editing, with follow-up Q&A and session management tools.5272MIT
- FlicenseAqualityCmaintenanceFastMCP server for image analysis providing OCR, metadata, and EXIF extraction.3
- AlicenseAqualityCmaintenanceAnalyzes images, audio, and video using Google's Gemini AI, with support for downloading videos from URLs such as Bilibili and YouTube.3MIT
- AlicenseAqualityAmaintenanceAn MCP server enabling Claude Code to analyze any video (local file, URL, or Jira ticket attachment) by extracting frame images and audio transcripts, or using Gemini for native video analysis.41MIT
- FlicenseAqualityBmaintenanceEnables AI agents to edit video using text-based proxies, motion graphics via Hyperframes, and advanced FFmpeg rendering, turning any LLM IDE into a professional video editor.4
- FlicenseAqualityCmaintenanceReverse-engineers design videos and images into structured frontend implementation specifications using vision LLMs and FFMPEG for frame-level analysis.11