Video Transcriber Mcp

Video Transcriber MCP Server

[](https://www.npmjs.com/package/video-transcriber-mcp) [](https://www.npmjs.com/package/video-transcriber-mcp) [](https://opensource.org/licenses/MIT)

A Model Context Protocol (MCP) server that transcribes videos from 1000+ platforms using whisper.cpp — 4-10x faster than Python Whisper. Built with TypeScript for type safety and available via npx for easy installation.

> 🦀 Prefer a standalone binary? Check out the Rust version, which embeds whisper.cpp directly (no external CLI needed) and adds an optional HTTP/REST API. Available on crates.io with cargo install video-transcriber-mcp.

✨ What's New

v2.0.0

• ⚡ whisper.cpp engine: switched from Python openai-whisper to whisper.cpp (via the whisper-cli binary) for 4-10x faster transcription with lower memory usage. ⚠️ Breaking: install whisper-cpp and download models (see [Prerequisites](#prerequisites)).
• 🛰️ Remote whisper worker: offload transcription to a GPU service with REMOTE_WHISPER_URL.
• 🍪 yt-dlp cookies: authenticate for age-restricted / members-only videos and bypass YouTube's bot check via YT_DLP_COOKIES or YT_DLP_COOKIES_FROM_BROWSER.
• 🧹 Transcript management tools: get_latest_transcript, delete_transcript, cleanup_old_transcripts, delete_all_transcripts.
• 📚 Smarter listing: list_transcripts now sorts newest-first and supports a limit.

Earlier

• 🌍 Multi-Platform Support: 1000+ video platforms (YouTube, Vimeo, TikTok, Twitter/X, Facebook, Instagram, Twitch, educational sites, and more) via yt-dlp
• 💻 Cross-Platform: Works on macOS, Linux, and Windows
• 🎛️ Configurable Whisper Models: Choose from tiny, base, small, medium, or large models
• 🌐 Language Support: Transcribe in 90+ languages or use auto-detection
• 🔄 Automatic Retries: Network failures are handled automatically with exponential backoff
• 🎯 Platform Detection: Automatically detects the video platform

⚠️ Legal Notice

This tool is intended for educational, accessibility, and research purposes only.

Before using this tool, please understand:

• Most platforms' Terms of Service generally prohibit downloading content
• You are responsible for ensuring your use complies with applicable laws
• This tool should primarily be used for:
• ✅ Your own content
• ✅ Creating accessibility features (captions for deaf/hard of hearing)
• ✅ Educational and research purposes (where permitted)
• ✅ Content you have explicit permission to download

Please read [LEGAL.md](LEGAL.md) for detailed legal information before using this tool.

We do not encourage or endorse violation of any platform's Terms of Service or copyright infringement. Use responsibly and ethically.

Features

• 🎥 Download audio from 1000+ video platforms (powered by yt-dlp)
• 📂 Transcribe local video files (mp4, avi, mov, mkv, and more)
• ⚡ Transcribe using whisper.cpp locally (no API key needed) — 4-10x faster than Python Whisper
• 🛰️ Optional remote whisper worker for GPU offload (REMOTE_WHISPER_URL)
• 🍪 yt-dlp cookie support for age-restricted / bot-checked videos
• 🎛️ Configurable Whisper models (tiny, base, small, medium, large)
• 🌐 Support for 90+ languages with auto-detection
• 📝 Generate transcripts in multiple formats (TXT, JSON, Markdown)
• 📚 List, read, and manage previous transcripts (list/latest/delete/cleanup)
• 🔌 Integrate seamlessly with Claude Code or any MCP client
• 🔒 Full type safety with TypeScript
• 🔍 Automatic dependency checking
• 🔄 Automatic retry logic for network failures
• 🎯 Platform detection (shows which platform you're transcribing from)

Supported Platforms

Thanks to yt-dlp, this tool supports 1000+ video platforms including:

• Social Media: YouTube, TikTok, Twitter/X, Facebook, Instagram, Reddit, LinkedIn
• Video Hosting: Vimeo, Dailymotion, Twitch
• Educational: Coursera, Udemy, Khan Academy, LinkedIn Learning, edX
• News: BBC, CNN, NBC, PBS
• Conference/Tech: YouTube (tech talks), Vimeo (conferences)
• And many, many more!

Run the list_supported_sites tool to see the complete list of 1000+ supported platforms.

Prerequisites

You need these tools installed: yt-dlp (video downloader), whisper.cpp (the whisper-cli binary), and ffmpeg (audio processing), plus at least one whisper.cpp model (see [Whisper Models](#whisper-models)). Deno is optional but recommended for rock-solid YouTube downloads — see the note below.

> 💡 YouTube reliability — Deno (recommended, not required). This tool passes yt-dlp the android extractor client, which serves most YouTube videos without a JavaScript runtime. For the occasional video the android client can't serve, yt-dlp needs a JS runtime to solve YouTube's signature / "n" challenge — otherwise that specific video fails with errors that look like bot-detection (No supported JavaScript runtime could be found, Signature solving failed, HTTP 403). Installing Deno ≥ 2.3.0 (yt-dlp auto-detects it) makes YouTube downloads robust across all videos. If you already have Deno, make sure it's ≥ 2.3.0 (deno --version, then deno upgrade) — an older one is detected but can't solve the challenge. Non-YouTube sites don't need it. Also keep yt-dlp current (yt-dlp -U) — an outdated yt-dlp is the more common cause of YouTube failures.

> If you set REMOTE_WHISPER_URL to offload transcription to a remote worker, you can skip installing whisper-cpp and downloading models locally.

macOS

brew install yt-dlp       # Video downloader (supports 1000+ sites)
brew install whisper-cpp  # whisper.cpp transcription (installs `whisper-cli`)
brew install ffmpeg       # Audio processing
brew install deno         # JS runtime — optional, recommended for YouTube reliability

Linux

# Ubuntu/Debian
sudo apt update
sudo apt install ffmpeg
pip install yt-dlp
curl -fsSL https://deno.land/install.sh | sh   # JS runtime — optional, recommended for YouTube reliability
# whisper.cpp: build from source, then put `whisper-cli` on your PATH
git clone https://github.com/ggerganov/whisper.cpp && cd whisper.cpp && make
# copy build/bin/whisper-cli to /usr/local/bin, or set WHISPER_CPP_BINARY to its path

Windows

# Install Python from python.org first
pip install yt-dlp

# Install ffmpeg (required) + deno (optional, recommended for YouTube) via Chocolatey
choco install ffmpeg
choco install deno   # JS runtime — optional, recommended for YouTube reliability

# whisper.cpp: download a prebuilt release from
# https://github.com/ggerganov/whisper.cpp/releases and put whisper-cli.exe on PATH,
# or set WHISPER_CPP_BINARY to its full path.

> Deno not on PATH? If you installed Deno but yt-dlp still reports "No supported JavaScript runtime" (common when the installer drops it in ~/.deno/bin), symlink it somewhere already on PATH — e.g. ln -sf ~/.deno/bin/deno ~/.local/bin/deno — or add ~/.deno/bin to your PATH.

Verify installations (all platforms)

yt-dlp --version
whisper-cli --help
ffmpeg -version
deno --version

Whisper Models

whisper.cpp uses ggml model files stored in ~/.cache/video-transcriber-mcp/models/. Download them with the bundled script:

# Download a single model (recommended: start with base)
bash scripts/download-models.sh base

# Or download everything
bash scripts/download-models.sh all

> Windows: download-models.sh is a Bash script — run it from Git Bash or WSL. Or download the model manually: grab ggml-base.bin (or another size) from and drop it into %USERPROFILE%\.cache\video-transcriber-mcp\models\.

| Model | Size | Notes | |--------|---------|-------------------------------| | tiny | ~75 MB | fastest, lowest accuracy | | base | ~142 MB | recommended default | | small | ~466 MB | good balance | | medium | ~1.5 GB | high accuracy | | large | ~2.9 GB | best accuracy, slowest |

Run the check_dependencies tool at any time to see which models are installed.

Quick Start

For End Users (Using npx)

Add to your Claude Code config (~/.claude/settings.json):

{
  "mcpServers": {
    "video-transcriber": {
      "command": "npx",
      "args": ["-y", "video-transcriber-mcp"]
    }
  }
}

Or use directly from GitHub:

{
  "mcpServers": {
    "video-transcriber": {
      "command": "npx",
      "args": [
        "-y",
        "github:nhatvu148/video-transcriber-mcp"
      ]
    }
  }
}

That's it! No installation needed. npx will automatically download and run the package.

For Local Development

# Clone the repository
git clone https://github.com/nhatvu148/video-transcriber-mcp.git
cd video-transcriber-mcp

# Install dependencies
npm install
# or
bun install

# Build the project
npm run build

# Use in Claude Code with local path
{
  "mcpServers": {
    "video-transcriber": {
      "command": "npx",
      "args": ["-y", "/path/to/video-transcriber-mcp"]
    }
  }
}

Usage

From Claude Code

Once configured, you can use these tools in Claude Code:

Transcribe a video from any platform

Please transcribe this YouTube video: https://www.youtube.com/watch?v=VIDEO_ID

Transcribe this TikTok video: https://www.tiktok.com/@user/video/123456789

Get the transcript from this Vimeo video with high accuracy: https://vimeo.com/123456789
(use model: large)

Transcribe this Spanish tutorial video: https://youtube.com/watch?v=VIDEO_ID
(language: es)

Transcribe a local video file

Transcribe this local video file: /Users/myname/Videos/meeting.mp4

Transcribe ~/Downloads/lecture.mov with high accuracy
(use model: medium)

Claude will use the transcribe_video tool automatically with optional parameters for model and language.

List all supported platforms

What platforms can you transcribe videos from?

List available transcripts

List all my video transcripts

Check dependencies

Check if my video transcriber dependencies are installed

Read a transcript

Show me the transcript for [video name]

Programmatic Usage

If you install the package:

npm install video-transcriber-mcp

You can import and use it programmatically:

import { transcribeVideo, checkDependencies, WhisperModel } from 'video-transcriber-mcp';

// Check dependencies — returns a human-readable status string
console.log(checkDependencies());

// Transcribe a video from URL with custom options
const result = await transcribeVideo({
  url: 'https://www.youtube.com/watch?v=VIDEO_ID',
  outputDir: '/path/to/output',
  model: 'medium', // tiny, base, small, medium, large
  language: 'en', // or 'auto' for auto-detection
  onProgress: (progress) => console.log(progress)
});

// Or transcribe a local video file
const localResult = await transcribeVideo({
  url: '/path/to/video.mp4',  // Local file path instead of URL
  outputDir: '/path/to/output',
  model: 'base',
  language: 'auto',
  onProgress: (progress) => console.log(progress)
});

console.log('Title:', result.metadata.title);
console.log('Platform:', result.metadata.platform);
console.log('Words:', result.wordCount);
console.log('Model:', result.modelUsed);
console.log('Files:', result.files);

Output

Transcripts are saved to ~/Downloads/video-transcripts/ by default.

For each video, three files are generated:

1. .txt - Plain text transcript
2. .json - JSON with video metadata, the transcript, and the model used
3. .md - Markdown with video metadata and formatted transcript

Example

~/Downloads/video-transcripts/
├── 7JBuA1GHAjQ-From-AI-skeptic-to-UNFAIR-advantage.txt
├── 7JBuA1GHAjQ-From-AI-skeptic-to-UNFAIR-advantage.json
└── 7JBuA1GHAjQ-From-AI-skeptic-to-UNFAIR-advantage.md

MCP Tools

transcribe_video

Transcribe videos from 1000+ platforms or local video files to text.

Parameters:

• url (required): Video URL from any supported platform OR path to a local video file (mp4, avi, mov, mkv, etc.)
• output_dir (optional): Output directory path
• model (optional): Whisper model - "tiny", "base" (default), "small", "medium", "large"
• language (optional): Language code (ISO 639-1: "en", "es", "fr", etc.) or "auto" (default)

Model Comparison: | Model | Speed | Accuracy | Use Case | |-------|-------|----------|----------| | tiny | ⚡⚡⚡⚡⚡ | ⭐⭐ | Quick drafts, testing | | base | ⚡⚡⚡⚡ | ⭐⭐⭐ | General use (default) | | small | ⚡⚡⚡ | ⭐⭐⭐⭐ | Better accuracy | | medium | ⚡⚡ | ⭐⭐⭐⭐⭐ | High accuracy | | large | ⚡ | ⭐⭐⭐⭐⭐⭐ | Best accuracy, slow |

list_transcripts

List all available transcripts with metadata, sorted by modification time (newest first).

Parameters:

• output_dir (optional): Directory to list
• limit (optional): Return only the N most recent transcripts

get_latest_transcript

Get the path and details of the most recently created/modified transcript. Useful to avoid accidentally reading an old transcript.

Parameters:

• output_dir (optional): Directory to search

delete_transcript

Delete a specific transcript by video ID (removes all associated .txt, .json, .md files).

Parameters:

• video_id (required): The video ID to delete (e.g. dQw4w9WgXcQ)
• output_dir (optional): Directory to delete from

cleanup_old_transcripts

Delete transcripts older than a given number of days.

Parameters:

• days (required): Delete files older than this many days
• output_dir (optional): Directory to clean

delete_all_transcripts

Delete ALL transcripts in the output directory. Cannot be undone.

Parameters:

• confirm (required): Must be true to actually delete
• output_dir (optional): Directory to clear

check_dependencies

Verify that all required dependencies (yt-dlp, ffmpeg, whisper.cpp) and models are installed.

list_supported_sites

List all 1000+ supported video platforms.

Environment Variables

All are optional. See [.env.example](.env.example) for details. When using the MCP server, set these in your client's env block.

| Variable | Description | |----------|-------------| | YT_DLP_COOKIES | Path to a Netscape-format cookies file (--cookies). Preferred on headless/Linux. | | YT_DLP_COOKIES_FROM_BROWSER | Browser to read cookies from (chrome, brave, edge, firefox, safari, …). Ignored if YT_DLP_COOKIES is set. | | REMOTE_WHISPER_URL | Offload transcription to a remote HTTP worker instead of running whisper.cpp locally. | | WHISPER_CPP_BINARY | Override the whisper.cpp CLI name/path (default whisper-cli). |

Example Claude Code config with cookies:

{
  "mcpServers": {
    "video-transcriber": {
      "command": "npx",
      "args": ["-y", "video-transcriber-mcp"],
      "env": {
        "YT_DLP_COOKIES_FROM_BROWSER": "chrome"
      }
    }
  }
}

Configuration Examples

Claude Code (Recommended)

{
  "mcpServers": {
    "video-transcriber": {
      "command": "npx",
      "args": ["-y", "video-transcriber-mcp"]
    }
  }
}

From GitHub (Latest)

{
  "mcpServers": {
    "video-transcriber": {
      "command": "npx",
      "args": ["-y", "github:nhatvu148/video-transcriber-mcp"]
    }
  }
}

Local Development

{
  "mcpServers": {
    "video-transcriber": {
      "command": "npx",
      "args": ["-y", "/absolute/path/to/video-transcriber-mcp"]
    }
  }
}

Development

Setup

# Install dependencies
npm install

# Build the project
npm run build

# Type check
npm run check

# Development mode (requires Bun)
bun run dev

# Clean build artifacts
npm r

…

## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [nhatvu148](https://github.com/nhatvu148)
- **Source:** [nhatvu148/video-transcriber-mcp](https://github.com/nhatvu148/video-transcriber-mcp)
- **License:** MIT

Install and usage instructions live in the source repository linked above.