io.github.AceDataCloud/mcp-wan

WanMCP

A Model Context Protocol (MCP) server for AI video generation using Wan through the AceDataCloud API.

Generate AI videos from text or images directly from Claude, VS Code, or any MCP-compatible client.

Features

• Text to Video - Create AI-generated videos from text prompts
• Image to Video - Generate videos using reference images
• Multiple Models - Support for 5 Wan models (wan2.6-t2v, wan2.6-i2v, wan2.6-r2v, wan2.6-i2v-flash, wan3.0-video)
• Multiple Resolutions - 480P (draft), 720P (default), 1080P (high quality)
• Audio Support - Generate videos with sound
• Character Transfer - Extract character appearance via reference videos (wan2.6-r2v)
• Task Tracking - Monitor generation progress and retrieve results

Tool Reference

Tool	Description
wan_generate_video	Generate AI video from a text prompt using Wan.
wan_generate_video_from_image	Generate AI video using a reference image as the starting frame.
wan_get_task	Query the status and result of a video generation task.
wan_get_tasks_batch	Query multiple video generation tasks at once.
wan_list_models	List all available Wan models for video generation.
wan_list_resolutions	List all available resolution options.
wan_list_actions	List all available Wan API actions and corresponding tools.

Quick Start

1. Get Your API Token

1. Sign up at AceDataCloud Platform
2. Go to the API documentation page
3. Click "Acquire" to get your API token
4. Copy the token for use below

2. Use the Hosted Server (Recommended)

AceDataCloud hosts a managed MCP server — no local installation required.

Endpoint: https://wan.mcp.acedata.cloud/mcp

All requests require a Bearer token. Use the API token from Step 1.

Claude.ai

Connect directly on Claude.ai with OAuth — no API token needed:

1. Go to Claude.ai Settings → Integrations → Add More
2. Enter the server URL: https://wan.mcp.acedata.cloud/mcp
3. Complete the OAuth login flow
4. Start using the tools in your conversation

Claude Desktop

Add to your config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "wan": {
      "type": "streamable-http",
      "url": "https://wan.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Cursor / Windsurf

Add to your MCP config (.cursor/mcp.json or .windsurf/mcp.json):

{
  "mcpServers": {
    "wan": {
      "type": "streamable-http",
      "url": "https://wan.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

VS Code (Copilot)

Add to your VS Code MCP config (.vscode/mcp.json):

{
  "servers": {
    "wan": {
      "type": "streamable-http",
      "url": "https://wan.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Or install the Ace Data Cloud MCP extension for VS Code, which registers the hosted MCP servers with one-click setup.

JetBrains IDEs

1. Go to Settings → Tools → AI Assistant → Model Context Protocol (MCP)
2. Click Add → HTTP
3. Paste:

{
  "mcpServers": {
    "wan": {
      "url": "https://wan.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Claude Code

Claude Code supports MCP servers natively:

claude mcp add wan --transport http https://wan.mcp.acedata.cloud/mcp \
  -h "Authorization: Bearer YOUR_API_TOKEN"

Or add to your project's .mcp.json:

{
  "mcpServers": {
    "wan": {
      "type": "streamable-http",
      "url": "https://wan.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Cline

Add to Cline's MCP settings (.cline/mcp_settings.json):

{
  "mcpServers": {
    "wan": {
      "type": "streamable-http",
      "url": "https://wan.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Amazon Q Developer

Add to your MCP configuration:

{
  "mcpServers": {
    "wan": {
      "type": "streamable-http",
      "url": "https://wan.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Roo Code

Add to Roo Code MCP settings:

{
  "mcpServers": {
    "wan": {
      "type": "streamable-http",
      "url": "https://wan.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Continue.dev

Add to .continue/config.yaml:

mcpServers:
  - name: wan
    type: streamable-http
    url: https://wan.mcp.acedata.cloud/mcp
    headers:
      Authorization: "Bearer YOUR_API_TOKEN"

Zed

Add to Zed's settings (~/.config/zed/settings.json):

{
  "language_models": {
    "mcp_servers": {
      "wan": {
        "url": "https://wan.mcp.acedata.cloud/mcp",
        "headers": {
          "Authorization": "Bearer YOUR_API_TOKEN"
        }
      }
    }
  }
}

cURL Test

# Health check (no auth required)
curl https://wan.mcp.acedata.cloud/health

# MCP initialize
curl -X POST https://wan.mcp.acedata.cloud/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"test","version":"1.0"}}}'

3. Or Run Locally (Alternative)

If you prefer to run the server on your own machine:

# Install from PyPI
pip install mcp-wan
# or
uvx mcp-wan

# Set your API token
export ACEDATACLOUD_API_TOKEN="your_token_here"

# Run (stdio mode for Claude Desktop / local clients)
mcp-wan

# Run (HTTP mode for remote access)
mcp-wan --transport http --port 8000

Claude Desktop (Local)

{
  "mcpServers": {
    "wan": {
      "command": "uvx",
      "args": ["mcp-wan"],
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your_token_here"
      }
    }
  }
}

Docker (Self-Hosting)

docker pull ghcr.io/acedatacloud/mcp-wan:latest
docker run -p 8000:8000 ghcr.io/acedatacloud/mcp-wan:latest

Clients connect with their own Bearer token — the server extracts the token from each request's Authorization header.

Available Models

Model	Description	Use Case
wan2.6-t2v	Text to video	Generate video from text prompts
wan2.6-i2v	Image to video	Standard image-to-video generation
wan2.6-r2v	Reference video-to-video	Character extraction and transfer
wan2.6-i2v-flash	Fast image to video	Quick preview, lower quality
wan3.0-video	Text to video	Video generation with optional media

Configuration

Environment Variables

Variable	Description	Default
ACEDATACLOUD_API_TOKEN	API token from AceDataCloud	Required
ACEDATACLOUD_API_BASE_URL	API base URL	https://api.acedata.cloud
WAN_DEFAULT_MODEL	Default video model	wan2.6-t2v
WAN_DEFAULT_RESOLUTION	Default resolution	720P
WAN_REQUEST_TIMEOUT	Request timeout in seconds	1800
LOG_LEVEL	Logging level	INFO

Command Line Options

mcp-wan --help

Options:
  --version          Show version
  --transport        Transport mode: stdio (default) or http
  --port             Port for HTTP transport (default: 8000)

Development

Setup Development Environment

# Clone repository
git clone https://github.com/AceDataCloud/WanMCP.git
cd WanMCP

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # or `.venv\Scripts\activate` on Windows

# Install with dev dependencies
pip install -e ".[dev,test]"

Run Tests

# Run unit tests
pytest

# Run with coverage
pytest --cov=core --cov=tools

# Run integration tests (requires API token)
pytest tests/test_integration.py -m integration

Code Quality

# Format code
ruff format .

# Lint code
ruff check .

# Type check
mypy core tools

Build & Publish

# Install build dependencies
pip install -e ".[release]"

# Build package
python -m build

# Upload to PyPI
twine upload dist/*

Project Structure

WanMCP/
├── core/                   # Core modules
│   ├── __init__.py
│   ├── client.py          # HTTP client for Wan API
│   ├── config.py          # Configuration management
│   ├── exceptions.py      # Custom exceptions
│   ├── oauth.py           # OAuth 2.1 provider
│   ├── server.py          # MCP server initialization
│   ├── types.py           # Type definitions
│   └── utils.py           # Utility functions
├── tools/                  # MCP tool definitions
│   ├── __init__.py
│   ├── video_tools.py     # Video generation tools
│   ├── task_tools.py      # Task query tools
│   └── info_tools.py      # Information tools
├── prompts/                # MCP prompts
│   └── __init__.py        # Prompt templates
├── tests/                  # Test suite
│   ├── conftest.py
│   └── __init__.py
├── deploy/                 # Deployment configs
│   └── production/
│       ├── deployment.yaml
│       ├── ingress.yaml
│       └── service.yaml
├── .env.example           # Environment template
├── CHANGELOG.md
├── Dockerfile             # Docker image for HTTP mode
├── docker-compose.yaml    # Docker Compose config
├── LICENSE
├── main.py                # Entry point
├── pyproject.toml         # Project configuration
└── README.md

API Reference

This server wraps the AceDataCloud Wan API:

• Wan Videos API - Video generation (text2video, image2video)
• Wan Tasks API - Task queries

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing)
5. Open a Pull Request

Documentation

Documentation

License

MIT License - see LICENSE for details.

Links

• AceDataCloud Platform
• Wan AI
• Model Context Protocol
• MCP Python SDK

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Made with love by AceDataCloud