Velora AI Video Studio MCP Server

The official Model Context Protocol (MCP) server for Velora AI Video Studio. This server allows any MCP-compatible AI assistant (like Claude Desktop) to:

• Browse Velora's subscription plans and credit allocations
• Check prices and credit costs for different AI models
• Create AI videos with scripts, voices, music, and subtitles
• Check video status and retrieve completed videos

🚀 Features

• get_velora_plans: List pricing, features, and compute credits for all plans.
• estimate_video_cost: Calculate the AI Video Credits required for a specific model and duration.
• list_ai_models: View all available video/image models and their pricing tiers.
• create_video: Generate a video using your Velora API key.
• check_video_status: Poll generation progress.
• get_video_result: Get the final download URL.

🛠️ Usage (Local STDIO)

For testing locally with Claude Desktop or running via npx:

# Build the server locally
npm install
npm run build

# Or run instantly via npx (No installation needed!)
npx -y velora-mcp-server

🤖 Adding to Claude Desktop

To easily integrate Velora Video Studio into Claude Desktop, add this block to your claude_desktop_config.json:

Mac: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "velora": {
      "command": "npx",
      "args": ["-y", "velora-mcp-server@latest"]
    }
  }
}

Restart Claude Desktop, and you'll be able to create videos right from your chat!

🌍 Deployment (HTTP / SSE for Smithery Listing)

To list this server permanently on the Smithery directory, it is configured to run as an HTTP/SSE server. You can deploy it for free on Render or Railway.

Option 1: Deploy on Render (Recommended)

1. Push this repository to GitHub.
2. Sign up at Render.com.
3. Click New > Web Service.
4. Connect your GitHub repository.
5. Render will automatically detect the render.yaml and Dockerfile config.
6. Make sure the Environment Variable PORT is set (e.g., 3000).
7. Deploy! Your server will be live at https://your-service-name.onrender.com.

Option 2: Deploy on Railway

1. Push this repository to GitHub.
2. Sign up at Railway.app.
3. Click New Project > Deploy from GitHub repo.
4. Railway will automatically detect the railway.json and Dockerfile config.
5. It will assign a domain automatically.

🔗 Submitting to Smithery

Once your server is deployed via Render or Railway:

1. Go to Smithery.ai
2. Submit your MCP server using the URL:
   • Provide the SSE endpoint: https://your-service-name.onrender.com/mcp
3. Fill out the description and list your tools.
4. Your server will now be permanently listed in the Smithery directory for 10,000+ users!

🔑 Authentication

Most read-only tools do not require authentication. However, video generation tools (create_video, check_video_status, get_video_result) require a Velora API key.

The AI assistant will prompt the user to provide their API key when using these tools. Users can generate their API keys at: https://velorastudio.in/settings/api-keys

Built by Velora AI