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Analyze videos with scenes, transcripts, visual descriptions, and storyboards.
The materials indicate a locally run open-source MCP video analysis server with no required secrets and no declared remote endpoints, with no clear high-risk red flags. However, it still has the normal ability to execute code and process local video data, and its community adoption and maintenance visibility are weak, so it should be used in a constrained environment.
The materials explicitly state that no keys or environment variables are required. No API tokens, account credentials, or other sensitive authentication data are requested, so credential exposure and misuse risk appear low.
No remote endpoints are declared, and the description does not mention cloud analysis or uploading video/audio content to third-party services. Based on the provided materials, there is no explicit data egress path.
The system checks confirm that this tool can execute code. As an MCP server, it is expected to run local processing pipelines and invoke video analysis-related programs/libraries. This is normal for this class of tool, but it still warrants caution as local execution capability.
Its functions include scene detection, audio transcription, visual description, and storyboard generation, which inherently require reading local video files and may produce intermediate/output files. The materials do not show requests for system permissions beyond its stated purpose, so this appears to be normal local data access aligned with functionality.
Having an auditable open-source repository is a positive factor that lowers overall risk. However, the source is a third-party registry, the license is undeclared, community adoption is 0 stars, and maintenance status is unknown, so supply-chain maturity and maintenance signals are weak; source and dependencies should be reviewed first.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "video-analyzer" yet — see the docs or source repo.
Analyze this video and output scene segmentation, visual descriptions for each scene, audio transcription, and an overall summary.
A scene-by-scene breakdown with timestamps, visual descriptions, transcript, and summary.
Generate a storyboard for this video, including shot order, key visual points per shot, voiceover suggestions, and pacing notes.
A production-ready storyboard that can be used to recreate or adapt the video.
Analyze the style fingerprint of these videos and extract editing rhythm, shot language, visual style, and reusable creation patterns.
A style fingerprint summary with reusable creative patterns and templates.
Analyze videos with frame extraction, scene detection, and metadata retrieval.
Extract video frames and metadata for LLM-powered video analysis workflows.
Use natural language to process, analyze, and stream audio and video.
Analyze images and videos with configurable model providers for visual understanding.
Analyze local or remote images with vision LLMs and generate descriptions.
Edit, subtitle, and transcode videos through AI-driven FFmpeg workflows.