A powerful Model Context Protocol (MCP) server for YouTube video transcription and metadata extraction.
YouTube MCP Server
A powerful Model Context Protocol (MCP) server for YouTube video transcription and metadata extraction. This server provides advanced tools for AI agents to retrieve video metadata and generate high-quality transcriptions with native language support.
🌟 Features
- Metadata Extraction: Retrieve comprehensive video details (title, description, views, duration, etc.) without downloading the video.
- Smart Transcription:
- In-Memory Processing: fast, efficient, and disk-I/O free pipeline.
- VAD (Voice Activity Detection): uses Silero VAD for precise segmentation.
- Multilingual Support: supports 99 languages.
- Translation: Transcribe to any supported language.
- Caching: Intelligent file-based caching to avoid redundant processing.
- Optimized Performance:
- Uses
yt-dlpfor robust extraction. - Hardware acceleration (MPS/CUDA) for Whisper inference.
- Parallel processing for transcription segments.
- Uses
🛠️ Prerequisites
- Python 3.10+
- ffmpeg: Required for audio processing.
- Mac:
brew install ffmpeg - Linux:
sudo apt install ffmpeg - Windows: Download and add to PATH.
- Mac:
📦 Installation
-
Clone the repository:
git clone https://github.com/mourad-ghafiri/youtube-mcp-server cd youtube-mcp-server -
Install dependencies: Using
uv(recommended):uv sync
⚙️ Configuration
The server configuration is located in src/youtube_mcp_server/config.py. You can adjust the following parameters:
Directories
TRANSCRIPTIONS_DIR: Directory where transcription JSON files are cached (default:"transcriptions").
Models
WHISPER_MODEL_NAME: OpenAI Whisper model to use. Options:"tiny","base","small","medium","large","turbo". (default:"tiny").Note: Larger models require more RAM and a GPU (CUDA/MPS).
SILERO_REPO/SILERO_MODEL: VAD model repository and ID.
Audio Processing
SAMPLING_RATE: Audio sampling rate for Whisper/VAD (default:16000Hz).SEGMENT_PADDING_MS: Padding added to each audio segment to avoid cutting off words (default:200ms).
Concurrency
MAX_WORKERS: Number of parallel threads for transcribing audio segments (default:4). Increasing this speeds up transcription but uses more CPU/Memory.
🚀 Usage
1. Start the Server
uv run main.py
The server runs on SSE (Server-Sent Events) transport at http://127.0.0.1:8000/sse.
2. Configure MCP Client
Add the server configuration to your MCP client:
{
"mcpServers": {
"youtube": {
"url": "http://127.0.0.1:8000/sse"
}
}
}
🛠️ Tools Reference
get_video_info
Retrieves metadata for a given YouTube video.
- Input:
url(string) - Output: JSON object with title, views, description, thumbnails, etc.
{ "id": "VIDEO_ID", "title": "Video Title", "description": "Video description...", "view_count": 1000000, "duration": 212, "uploader": "Channel Name", "upload_date": "20091025", "thumbnail": "https://i.ytimg.com/...", "tags": ["tag1", "tag2"], "categories": ["Music"] }
transcribe_video
Transcribes a video with optional translation.
- Inputs:
url(string): Video URL.language(string, default="auto"):"auto": Transcribe in detected language."en": Translate to English."fr","es", etc.: Transcribe in specific language.
- Output: JSON with segments and metadata.
{ "id": "VIDEO_ID", "title": "Video Title", "duration": 212, "transcription": [ { "from": "00:00:00", "to": "00:00:05", "transcription": "First segment text..." }, { "from": "00:00:05", "to": "00:00:10", "transcription": "Second segment text..." } ] }
🏗️ Technical Architecture
- Services:
DownloadService,VADService(Silero),WhisperService(OpenAI),CacheService. - In-Memory Pipeline: Audio is downloaded -> loaded to RAM -> segmented by VAD -> transcribed by Whisper -> Cached.
- Concurrency: Parallel segment transcription.
🌍 Appendix: Supported Languages
| Country (Primary/Region) | Language | Code | |:-------------------------|:---------|:-----| | South Africa | Afrikaans | af | | Ethiopia | Amharic | am | | Arab World | Arabic | ar | | India | Assamese | as | | Azerbaijan | Azerbaijani | az | | Russia | Bashkir | ba | | Belarus | Belarusian | be | | Bulgaria | Bulgarian | bg | | Bangladesh | Bengali | bn | | Tibet | Tibetan | bo | | France (Brittany) | Breton | br | | Bosnia and Herzegovina | Bosnian | bs | | Spain (Catalonia) | Catalan | ca | | Czech Republic | Czech | cs | | Wales | Welsh | cy | | Denmark | Danish | da | | Germany | German | de | | Greece | Greek | el | | USA / UK | English | en | | Spain | Spanish | es | | Estonia | Estonian | et | | Spain (Basque) | Basque | eu | | Iran | Persian | fa | | Finland | Finnish | fi | | Faroe Islands | Faroese | fo | | France | French | fr | | Spain (Galicia) | Galician | gl | | India | Gujarati | gu | | Nigeria | Hausa | ha | | Hawaii | Hawaiian | haw | | Israel | Hebrew | he | | India | Hindi | hi | | Croatia | Croatian | hr | | Haiti | Haitian Creole | ht | | Hungary | Hungarian | hu | | Armenia | Armenian | hy | | Indonesia | Indonesian | id | | Iceland | Icelandic | is | | Italy | Italian | it | | Japan | Japanese | ja | | Indonesia (Java) | Javanese | jw | | Georgia | Georgian | ka | | Kazakhstan | Kazakh | kk | | Cambodia | Khmer | km | | India | Kannada | kn | | South Korea | Korean | ko | | Ancient Rome | Latin | la | | Luxembourg | Luxembourgish | lb | | Congo | Lingala | ln | | Laos | Lao | lo | | Lithuania | Lithuanian | lt | | Latvia | Latvian | lv | | Madagascar | Malagasy | mg | | New Zealand | Maori | mi | | North Macedonia | Macedonian | mk | | India | Malayalam | ml | | Mongolia | Mongolian | mn | | India | Marathi | mr | | Malaysia | Malay | ms | | Malta | Maltese | mt | | Myanmar | Myanmar | my | | Nepal | Nepali | ne | | Netherlands | Dutch | nl | | Norway | Nynorsk | nn | | Norway | Norwegian | no | | France (Occitania) | Occitan | oc | | India (Punjab) | Punjabi | pa | | Poland | Polish | pl | | Afghanistan | Pashto | ps | | Portugal / Brazil | Portuguese | pt | | Romania | Romanian | ro | | Russia | Russian | ru | | India | Sanskrit | sa | | Pakistan | Sindhi | sd | | Sri Lanka | Sinhala | si | | Slovakia | Slovak | sk | | Slovenia | Slovenian | sl | | Zimbabwe | Shona | sn | | Somalia | Somali | so | | Albania | Albanian | sq | | Serbia | Serbian | sr | | Indonesia | Sundanese | su | | Sweden | Swedish | sv | | East Africa | Swahili | sw | | India | Tamil | ta | | India | Telugu | te | | Tajikistan | Tajik | tg | | Thailand | Thai | th | | Turkmenistan | Turkmen | tk | | Philippines | Tagalog | tl | | Turkey | Turkish | tr | | Russia (Tatarstan) | Tatar | tt | | Ukraine | Ukrainian | uk | | Pakistan | Urdu | ur | | Uzbekistan | Uzbek | uz | | Vietnam | Vietnamese | vi | | Ashkenazi Jewish | Yiddish | yi | | Nigeria | Yoruba | yo | | China (Guangdong) | Cantonese | yue | | China | Chinese | zh |
🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the project
- Create your feature branch (
git checkout -b feature/AmazingFeature) - Commit your changes (
git commit -m 'Add some AmazingFeature') - Push to the branch (
git push origin feature/AmazingFeature) - Open a Pull Request
📄 License
Distributed under the MIT License. See LICENSE for more information.
Built with love ❤️