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MCP Video Analyzer

by guimatheus92

Analyze video URLs and local files for transcripts, frames, OCR text, timelines, and metadata through MCP.

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Install MCP Video Analyzer

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "guimatheus92-mcp-video-analyzer": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-video-analyzer@latest"
      ]
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Install not yet sandbox-tested— we haven't run this command through our automated sandbox yet. Not a red flag; we're working through the catalog.

Overview

The guimatheus92/mcp-video-analyzer MCP server analyzes online videos and local files, returning transcripts, key frames, OCR text, timelines, and metadata. It supports Loom, direct video files, and platforms handled through yt-dlp, including YouTube, Vimeo, TikTok, Instagram, X, Twitch, Dailymotion, and Facebook. Use it when an agent needs to inspect both spoken content and visual details, such as on-screen text or changes at a specific timestamp. It runs locally over MCP stdio and requires no authentication, while yt-dlp improves support for several platform URLs.

Use cases

  • Extract transcripts and timestamps from recorded meetings
  • Find on-screen error messages with OCR
  • Inspect a video moment using frame bursts
  • Process multiple video URLs in a resumable batch
  • Retrieve video metadata without downloading frames

Key features

  • Full transcript, frame, OCR, timeline, and metadata analysis
  • Batch analysis with resumable results
  • Scene-change and dense temporal frame extraction
  • Timestamp and time-range visual inspection
  • Native caption and Whisper transcription paths
  • Support for platform URLs, direct files, and local videos

Tools8

What MCP Video Analyzer lets your agent do. Expand a tool for its parameters.

Self-reported~127 tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 1d ago

Recent health check succeeded.

96/96 checks healthy over the last 22d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 5d ago via OSV.dev · mcp-video-analyzer@latest (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars102Stargazers on the source repository.
npm downloads1kPackage downloads in the last 30 days.
Last commit2d agoMost recent push to the default branch.
Tools exposed8Callable tools this server registers over MCP.
Directory activity3 installs · 3 upvotesConfig copies, upvotes, and views on AllMCPs.

How MCP Video Analyzer works

What guimatheus92/mcp-video-analyzer MCP server does

The guimatheus92/mcp-video-analyzer MCP server turns video sources into structured information that an AI agent can inspect. Inputs can include supported platform URLs, direct video links such as .mp4 or .webm, Loom links, and local video files. Results can combine speech transcripts, extracted frames, OCR text, a time-aligned timeline, and video metadata.

The full analysis operation can also include comments, chapters, and an AI summary when those details are available from the source. For narrower tasks, the server exposes separate operations for transcripts, metadata, frames, individual timestamps, and short frame bursts. This lets an agent request only the data needed for a particular question.

How it works

The guimatheus92/mcp-video-analyzer MCP server exposes eight MCP tools:

  • analyze_video returns a complete analysis.
  • analyze_videos processes multiple sources and produces one structured result per source, with resumable batch processing.
  • get_transcript uses native captions when available and can fall back to Whisper.
  • get_metadata retrieves metadata, comments, and chapters without downloading the video.
  • get_frames extracts key frames using scene changes or dense one-frame-per-second sampling.
  • analyze_moment examines a selected time range using burst frames, transcript content, and OCR.
  • get_frame_at returns one frame at a requested timestamp.
  • get_frame_burst samples several frames from a narrow interval for motion or animation inspection.

Frame extraction can use yt-dlp and the bundled ffmpeg-static package. Chrome or Chromium provides an optional fallback. Static videos without scene changes can use uniform temporal sampling so frame and OCR results are still available.

Setup and configuration

Run the server with Node.js 22.12 or newer. The package starts as an MCP stdio server with npx mcp-video-analyzer@latest; the README also provides an executable npx -y mcp-video-analyzer@latest form for command-line use. MCP clients can register the package as a stdio process.

The guimatheus92/mcp-video-analyzer MCP server does not require credentials. Install yt-dlp separately for YouTube, Vimeo, TikTok, Instagram, X, Twitch, Dailymotion, and Facebook URLs. It is optional for direct URLs and local files, and can improve Loom downloads. Without yt-dlp or Chrome, direct files and local files can still use ffmpeg-based frame extraction, while platform URLs may produce an install warning.

The bundled one-shot CLI accepts an input source and can write frame images to a selected output directory. MCP_CACHE_DIR can relocate the persistent cache, and MCP_FRAME_MAX_WIDTH can set a default frame width limit. CLI options also control detail level, frame count, OCR languages, Whisper settings, output fields, refresh behavior, and output location.

Tools and capabilities

Choose get_metadata when downloading frames is unnecessary, get_transcript for speech-only workflows, or get_frame_at and get_frame_burst for targeted visual checks. Use analyze_moment to investigate a known interval, and analyze_videos for multiple sources. The complete tool combines transcript, visual, OCR, timeline, and metadata results in one response.

Limitations and notes

Platform coverage depends on yt-dlp and the source being accessible. Transcription may rely on native captions or the Whisper fallback, and comments, chapters, and AI summaries are available only when supported by the source. Partial processing problems are reported as warnings; hard failures are distinct from those partial results. The server performs local processing and stores extracted frame files in a cache unless an output location is specified.

Read the full README View source on GitHub

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Frequently Asked Questions about MCP Video Analyzer

Install Node.js 22.12 or newer, then register `npx mcp-video-analyzer@latest` as an MCP stdio server. Install yt-dlp separately when analyzing supported platform URLs.

Yes. Add an MCP server entry that runs `npx` with `mcp-video-analyzer@latest`, then restart Claude Desktop.

Yes. Its full analysis and moment-analysis tools include OCR, and frame extraction can use scene changes or dense temporal sampling.

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