guimatheus92/mcp-video-analyzer
by Various
MCP server for video analysis — extracts transcripts, key frames, OCR text, and metadata from video URLs. Supports Loom and direct video files.
MCP
guimatheus92/mcp-video-analyzer
Added 1 June 2026
Overview
An MCP server that extracts transcripts, key frames, OCR text, and metadata from video URLs. It supports Loom and direct video files, enabling programmatic video analysis through the Model Context Protocol.
Best for
Best for
Developers needing to automate video content extraction within MCP-compatible workflows
Use cases
- Extract transcripts and key frames from Loom recordings
- Perform OCR on video frames to capture on-screen text
- Retrieve metadata from direct video file URLs
How to use
Install
npx skills add guimatheus92/mcp-video-analyzer Tools exposed
YTDLP_COOKIESYTDLP_COOKIES_FROM_BROWSERWHISPER_MODELWHISPER_LANGUAGEWHISPER_PROMPTWHISPER_BINWHISPER_DEVICEWHISPER_COMPUTEWHISPER_BEAM_SIZEWHISPER_WORD_TIMESTAMPSWHISPER_HF_MODELOPENAI_API_KEY
Tested with
Claude Desktop, Claude Code, Cursor, VS Code, ChatGPT
Notes
An MCP server that extracts transcripts, key frames, OCR text, and metadata from video URLs. It supports Loom and direct video files, enabling programmatic video analysis through the Model Context Protocol.
9 stars on GitHub. Last updated 2026-03-27. Licensed MIT.
Use cases
- Extract transcripts and key frames from Loom recordings
- Perform OCR on video frames to capture on-screen text
- Retrieve metadata from direct video file URLs
Pros
- Supports both Loom and direct video file inputs
- Provides multiple extraction types (transcript, frames, OCR, metadata)
- Lightweight TypeScript implementation with few dependencies
Cons
- Limited to video URLs, no local file upload support
- No built-in error handling for unsupported video formats
- Small community and limited documentation beyond the README
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Supports both Loom and direct video file inputs
- Provides multiple extraction types (transcript, frames, OCR, metadata)
- Lightweight TypeScript implementation with few dependencies
Cons
- Limited to video URLs, no local file upload support
- No built-in error handling for unsupported video formats
- Small community and limited documentation beyond the README
Pairs with
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