Is Videoscan Mcp safe to install?

SaferSkills independently audited Videoscan Mcp (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.

CategoryWeightCategory scoreContribution

Securityprompt, exec, net, exfil, eval

35%

100

35.0 pts

Supply chainhash, typosquat, maintainer, lockfile

20%

100

20.0 pts

Maintenancestaleness, pinning, CI

15%

100

15.0 pts

TransparencySKILL.md, perms, README

15%

100

15.0 pts

Communityinstalls, verify, response

15%

100

15.0 pts

Findings & checks · 0 flagged

Securityscore 100 · 0 findings

✓—All security checks passedNo findings in this category for the latest scan.pass

Supply chainscore 100 · 0 findings

✓—All supply chain checks passedNo findings in this category for the latest scan.pass

Maintenancescore 100 · 0 findings

✓—All maintenance checks passedNo findings in this category for the latest scan.pass

Transparencyscore 100 · 0 findings

✓—All transparency checks passedNo findings in this category for the latest scan.pass

Communityscore 100 · 0 findings

✓—All community checks passedNo findings in this category for the latest scan.pass

The primary manifest — the file an agent reads to learn what this artifact does.

README.md · 1 file

README.md8.7 KB · Markdown

VideoScan MCP

An MCP (Model Context Protocol) server for comprehensive video analysis — AI-powered transcription, visual frame analysis, and metadata extraction from 1000+ platforms.

Features

Full video analysis — combines transcription, frame extraction, and metadata in a single call
AI vision analysis — describes frames and extracts on-screen text (OCR) using GPT-4o, Claude, or Gemini
Audio transcription — Whisper-based transcription with timestamps and language detection
Auto-tuning — automatically adjusts frame extraction density, interval, and detail level based on video duration
Smart frame extraction — scene-change detection, interval sampling, or combined strategy
Deduplication — perceptual hashing removes near-duplicate frames before analysis
Metadata extraction — title, duration, chapters, tags, view count, and more without full download
Multi-provider — OpenAI, Anthropic, and Google vision providers with per-request override
Caching — persistent cache for downloads, frames, and results to minimize repeat costs
1000+ platforms — powered by yt-dlp (YouTube, Vimeo, Twitter/X, TikTok, and more)

Installation

pip install videoscan-mcp

System dependencies

VideoScan requires ffmpeg for video processing and yt-dlp for downloading from URLs.

# macOS
brew install ffmpeg yt-dlp

# Ubuntu/Debian
apt install ffmpeg
pip install yt-dlp

# Windows — install ffmpeg from https://ffmpeg.org/download.html, then:
pip install yt-dlp

Configuration

Copy .env.example to .env and fill in at minimum one API key:

# Vision provider (frame analysis)
VISION_PROVIDER=openai          # openai | anthropic | google
VISION_MODEL=                   # optional — defaults: gpt-4o / claude-sonnet-4-20250514 / gemini-2.0-flash

# Transcription provider
TRANSCRIPTION_PROVIDER=openai   # openai only for now
TRANSCRIPTION_MODEL=whisper-1

# Concurrency
VISION_CONCURRENCY=5            # max parallel vision API calls

# API keys — only need the key for your chosen provider
OPENAI_API_KEY=sk-...
ANTHROPIC_API_KEY=sk-ant-...
GOOGLE_API_KEY=AIza...

# Cache
CACHE_ENABLED=true
CACHE_DIR=~/.videoscan/cache
CACHE_MAX_SIZE_GB=5
CACHE_DOWNLOAD_TTL=3600         # 1 hour
CACHE_FRAMES_TTL=86400          # 24 hours
CACHE_RESULTS_TTL=604800        # 7 days

# Safety limits (set to 0 for unlimited)
MAX_VIDEO_DURATION=3600         # 60 minutes in seconds
MAX_DOWNLOAD_SIZE=2147483648    # 2 GB in bytes
MAX_ANALYZED_FRAMES=100
DOWNLOAD_TIMEOUT=300
FRAME_ANALYSIS_TIMEOUT=30

Quick Start — Claude Code

Add VideoScan to your Claude Code settings.json (usually at ~/.claude/settings.json):

{
  "mcpServers": {
    "videoscan": {
      "command": "videoscan",
      "env": {
        "OPENAI_API_KEY": "sk-..."
      }
    }
  }
}

Or using uvx without a global install:

{
  "mcpServers": {
    "videoscan": {
      "command": "uvx",
      "args": ["videoscan-mcp"],
      "env": {
        "OPENAI_API_KEY": "sk-..."
      }
    }
  }
}

Once connected, you can ask Claude things like:

"Analyze this YouTube video: https://youtube.com/watch?v=..."
"Transcribe the audio from this video file"
"What's on screen at the 2:30 mark of this video?"
"Extract frames from this video and describe what you see"

Auto-Tuning

When max_frames and interval are not explicitly set, VideoScan automatically adjusts frame extraction parameters based on video duration to optimize cost and coverage:

Duration	Frames	Interval	Strategy	Detail
< 2 min	~1/sec (dense)	1s	combined	detailed
2–10 min	~40	3s	combined	standard
10–30 min	~30	10s	combined	standard
30–60 min	~30	20s	combined	brief
> 60 min	~20	30s	scene only	brief

Short videos get dense frame extraction for maximum detail, while longer videos use lighter sampling to keep costs down. You can always override by setting max_frames or interval explicitly.

Tool Reference

`analyze_video`

Full pipeline — transcription + AI frame analysis + metadata in one call. Uses auto-tuning by default.

Parameter	Type	Default	Description
`source`	string	required	URL or local file path
`detail`	string	`"standard"`	Vision level: `"brief"`, `"standard"`, `"detailed"`
`max_frames`	int	auto	Maximum frames to analyze — set to `-1` (default) for auto-tuning based on duration
`threshold`	float	`0.3`	Scene change sensitivity (0.0–1.0)
`strategy`	string	`"combined"`	Frame extraction: `"scene"`, `"interval"`, `"combined"`
`interval`	int	auto	Seconds between frames — set to `-1` (default) for auto-tuning based on duration
`skip_frames`	bool	`false`	Skip visual analysis (transcription only)
`skip_audio`	bool	`false`	Skip transcription (frames only)
`language`	string	`"auto"`	Transcription language or `"auto"`
`provider`	string	`null`	Override vision provider
`force_refresh`	bool	`false`	Bypass cache

`transcribe`

Transcribe video or audio to text with timestamps.

Parameter	Type	Default	Description
`source`	string	required	URL or local file path
`language`	string	`"auto"`	Preferred language or `"auto"` for detection

`extract_frames`

Extract and AI-analyze frames from a video.

Parameter	Type	Default	Description
`source`	string	required	URL or local file path
`max_frames`	int	`30`	Maximum frames to extract (1–100)
`threshold`	float	`0.3`	Scene change sensitivity (0.0–1.0)
`strategy`	string	`"combined"`	`"scene"`, `"interval"`, or `"combined"`
`interval`	int	`5`	Seconds between frames in interval mode
`detail`	string	`"standard"`	Vision analysis level
`deduplicate`	bool	`true`	Remove near-duplicate frames via dHash
`provider`	string	`null`	Override vision provider
`force_refresh`	bool	`false`	Bypass cache

`analyze_moment`

Deep-dive analysis on a specific time range.

Parameter	Type	Default	Description
`source`	string	required	URL or local file path
`start`	float	required	Start time in seconds
`end`	float	required	End time in seconds
`dense`	bool	`true`	Extract 1 frame per second in the range
`detail`	string	`"detailed"`	Vision analysis level
`provider`	string	`null`	Override vision provider
`force_refresh`	bool	`false`	Bypass cache

`get_frame_at`

Get a single frame at a specific timestamp, optionally analyzed by AI.

Parameter	Type	Default	Description
`source`	string	required	URL or local file path
`timestamp`	float	required	Time in seconds
`analyze`	bool	`true`	Run AI vision analysis
`provider`	string	`null`	Override vision provider
`force_refresh`	bool	`false`	Bypass cache

`get_metadata`

Fetch video metadata without downloading the full video.

Parameter	Type	Default	Description
`source`	string	required	URL or local file path
`include`	list	`null`	Specific fields to return — `"title"`, `"duration"`, `"channel"`, `"description"`, `"thumbnail"`, `"chapters"`, `"tags"`, `"view_count"`. Returns all if omitted.

Supported Platforms

VideoScan uses yt-dlp under the hood, which supports 1000+ video platforms including:

YouTube, YouTube Shorts, YouTube Live
Vimeo, Dailymotion, Twitch
Twitter/X, Instagram, TikTok, Facebook
Reddit, LinkedIn, Pinterest
BBC iPlayer, CNN, NBC, CBS
SoundCloud, Bandcamp (audio)
And hundreds more — see the yt-dlp supported sites list

Local files in any format supported by ffmpeg (mp4, mov, avi, mkv, webm, mp3, wav, etc.) are also supported.

Cost Estimates

Costs depend on your chosen provider and usage:

Operation	Provider	Approx. Cost
Vision analysis	OpenAI GPT-4o	~$0.015 per frame
Vision analysis	Anthropic Claude	~$0.024 per frame
Vision analysis	Google Gemini	~$0.002 per frame
Transcription	OpenAI Whisper	~$0.006 per minute

A typical 10-minute video analyzed with analyze_video (30 frames + transcription) costs approximately $0.45–$0.51 with OpenAI.

Development

git clone https://github.com/guguborbh/videoscan-mcp
cd videoscan-mcp
pip install -e ".[dev]"
pytest

License

MIT License — see LICENSE for details.

Videoscan Mcp— agent skill

Is Videoscan Mcp safe to install?

VideoScan MCP

Features

Installation

System dependencies

Configuration

Quick Start — Claude Code

Auto-Tuning

Tool Reference

`analyze_video`

`transcribe`

`extract_frames`

`analyze_moment`

`get_frame_at`

`get_metadata`

Supported Platforms

Cost Estimates

Development

License

Audit the pieces. Scan the whole. Decide.