MCP Video Cloud Server

MCP Video Cloud Server

Downloads videos from 1000+ social media platforms and stores them in S3-compatible cloud storage, returning public URLs for videos, audio, transcripts, and thumbnails.

Category
Visit Server

README

MCP Video Cloud Server

A Remote Model Context Protocol (MCP) server that downloads videos from social media platforms (YouTube, Facebook, Instagram, TikTok, etc.) and stores them in S3-compatible cloud storage, returning publicly accessible URLs.

โœจ Optimized for Smithery.ai deployment - Deploy in minutes with one-click setup!

๐Ÿš€ Quick Deploy to Smithery.ai

  1. Fork this repository to your GitHub account
  2. Set up Cloudflare R2 (or AWS S3) storage
  3. Deploy on Smithery.ai - Click "Deploy" and connect your GitHub repo
  4. Configure your S3 credentials in Smithery's interface
  5. Start using - Connect to Claude Desktop and download videos!

๐Ÿ‘‰ See detailed deployment instructions

โœจ Features

  • Multi-Platform Support: Download from 1000+ sites via yt-dlp
  • Cloud Storage: Automatic upload to S3/R2 with public URLs
  • Transcript Extraction: Get clean text transcripts
  • Thumbnail Extraction: Extract video thumbnails
  • Audio Extraction: Extract audio in MP3 format
  • Metadata Retrieval: Get comprehensive video information
  • Remote Access: Runs in the cloud, no local setup needed
  • Smithery Integration: One-click deployment and scaling

๐ŸŽฏ Supported Platforms

  • YouTube
  • Facebook
  • Instagram
  • TikTok
  • Twitter/X
  • Vimeo
  • Twitch
  • And 1000+ other sites

๐Ÿ› ๏ธ Available Tools

download_video_to_cloud

Download a video and store it in cloud storage.

  • Input: Video URL, quality preference
  • Output: Public URL, filename, file size, metadata

download_audio_to_cloud

Extract audio from a video and store it in cloud storage.

  • Input: Video URL
  • Output: Public URL, filename, file size, metadata

extract_transcript_to_cloud

Extract subtitles/transcript and store as clean text.

  • Input: Video URL, language code
  • Output: Public URL, filename, transcript preview

extract_thumbnail_to_cloud

Extract video thumbnail and store it in cloud storage.

  • Input: Video URL
  • Output: Public URL, filename

get_video_metadata

Get comprehensive video information without downloading.

  • Input: Video URL
  • Output: Title, uploader, duration, views, description, etc.

๐Ÿ”ง Configuration

The server requires S3-compatible storage configuration:

s3Endpoint: https://your-account.r2.cloudflarestorage.com
s3Region: auto
s3AccessKeyId: your-access-key
s3SecretAccessKey: your-secret-key
s3BucketName: your-bucket-name
s3PublicUrlBase: https://your-custom-domain.com  # Optional

๐Ÿ“ File Organization

Files are organized in your S3 bucket:

  • videos/ - Downloaded video files
  • audio/ - Extracted audio files
  • transcripts/ - Transcript text files
  • thumbnails/ - Thumbnail images

๐Ÿ”’ Security & Privacy

  • All files stored in your own S3 bucket
  • No data permanently stored on the server
  • Temporary files automatically cleaned up
  • Credentials securely managed by Smithery
  • Server runs in isolated containers

๐Ÿ’ฐ Cost Considerations

  • Smithery Hosting: Check current pricing plans
  • Cloudflare R2: ~$0.015/GB/month storage + bandwidth
  • Processing: Included in Smithery hosting

๐Ÿƒโ€โ™‚๏ธ Local Development

If you want to run locally for development:

Prerequisites

  • Node.js 20+
  • yt-dlp installed
  • S3 credentials

Setup

git clone <your-fork>
cd mcp-video-cloud-server
npm install
npm run build:stdio

Environment Variables

S3_ENDPOINT=your-endpoint
S3_REGION=auto
S3_ACCESS_KEY_ID=your-key
S3_SECRET_ACCESS_KEY=your-secret
S3_BUCKET_NAME=your-bucket

Run

npm run start:stdio

๐Ÿงช Testing with Smithery

Use Smithery's development environment:

npm run dev

This starts a development server with the Smithery playground for testing.

๐Ÿค Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Test with npm run dev
  5. Submit a pull request

๐Ÿ“„ License

MIT License - see LICENSE file for details

๐Ÿ†˜ Support

  • Deployment Issues: Check DEPLOYMENT.md
  • Smithery Support: Visit https://smithery.ai/support
  • Bug Reports: Create a GitHub issue
  • Feature Requests: Create a GitHub issue

Ready to deploy? ๐Ÿ‘‰ Follow the deployment guide

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured