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Sisif AI Video Generation MCP Server

PyPI version Python 3.8+ License: MIT CI

A Model Context Protocol (MCP) server that provides tools for generating AI videos using the Sisif AI Video API. Seamlessly integrate AI video generation into Claude Desktop, IDEs, and other MCP-compatible clients.

🎥 Features

  • 🎬 Video Generation: Create AI-generated videos from text prompts

  • 📊 Status Monitoring: Track video generation progress with visual indicators

  • 🗂️ Video Management: List, search, and organize your generated videos

  • 🔄 Smart Retry Logic: Automatic error handling with exponential backoff

  • 🎨 Rich Formatting: Beautiful markdown output with emojis and status indicators

  • ⚡ High Performance: Async/await architecture for optimal speed

  • 🔒 Type Safe: Full Pydantic type validation and safety

Related MCP server: vimax-mcp

🚀 Quick Start

1. Installation

pip install sisif-mcp-server

2. Get Your API Key

  1. Sign up at sisif.ai

  2. Go to API Keys

  3. Create a new API key

3. Set Environment Variables

export SISIF_API_KEY="sk_live_your_api_key_here"

4. Configure Your MCP Client

For Claude Desktop

Add to your configuration file:

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

{
  "mcpServers": {
    "sisif": {
      "command": "sisif-mcp-server",
      "env": {
        "SISIF_API_KEY": "sk_live_your_api_key_here"
      }
    }
  }
}

For Other MCP Clients

The server works with any MCP-compatible client. Just use the sisif-mcp-server command with your API key in the environment.

📖 Usage Examples

Once configured, you can interact with the server naturally through your MCP client:

Generate a Video

Generate a 10-second video of "A majestic eagle soaring over snow-capped mountains at sunset" in high resolution

Check Video Status

What's the status of video 12345?

List Your Videos

Show me my recent videos

Monitor API Health

Is the Sisif API working properly?

Available Tools

1. generate_video

Generate a new AI video from a text prompt.

Parameters:

  • prompt (string, required): Text description of the video content

  • duration (integer, optional): Video duration in seconds (5-60, default: 5)

  • resolution (string, optional): Video resolution ("low", "medium", "high", default: "low")

Example:

{
  "name": "generate_video",
  "arguments": {
    "prompt": "A beautiful sunset over the ocean with waves gently crashing",
    "duration": 10,
    "resolution": "medium"
  }
}

2. check_video_status

Check the generation status of a video.

Parameters:

  • video_id (integer, required): The ID of the video to check

Example:

{
  "name": "check_video_status", 
  "arguments": {
    "video_id": 123
  }
}

3. get_video_details

Get detailed information about a specific video.

Parameters:

  • video_id (integer, required): The ID of the video

4. list_videos

List all videos for the authenticated user.

Parameters:

  • limit (integer, optional): Maximum number of videos to return (default: 10)

  • offset (integer, optional): Number of videos to skip (default: 0)

5. get_api_health

Check the health status of the Sisif API.

Configuration

The server can be configured using environment variables:

  • SISIF_API_KEY: Your Sisif API key (required)

  • SISIF_API_URL: Base URL for the Sisif API (default: "https://sisif.ai/api")

  • SISIF_TIMEOUT: Request timeout in seconds (default: 30)

  • SISIF_MAX_RETRIES: Maximum number of retries for failed requests (default: 3)

Development

  1. Install development dependencies:

pip install -e ".[dev]"
  1. Run tests:

pytest
  1. Format code:

black .
  1. Type checking:

mypy .

API Documentation

For complete API documentation, visit: https://sisif.ai/api/

🔧 Development

Setup Development Environment

git clone https://github.com/vtemian/sisif-ai-mcp.git
cd mcp-server
pip install -e ".[dev]"

Run Tests

make test
# or
pytest

Code Formatting

make format
# or  
black sisif_mcp_server/ tests/

Type Checking

make lint
# or
mypy sisif_mcp_server/

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

  1. Fork the repository

  2. Create your feature branch (git checkout -b feature/amazing-feature)

  3. Commit your changes (git commit -m 'Add some amazing feature')

  4. Push to the branch (git push origin feature/amazing-feature)

  5. Open a Pull Request

📝 Changelog

See CHANGELOG.md for a list of changes and versions.

🆘 Support

For support and questions:

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments


Made with ❤️ by Sisif AI

A
license - permissive license
-
quality - not tested
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maintenance

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