MCP server for Wan AI video generation. Published as the mcp-wan package (shown via PyPI version and downloads badges) and described as compatible with the Model Context Protocol (MCP). The project indicates Python requirement of 3.10+ and is licensed under MIT.

🛠️ Key Features

Model Context Protocol (MCP)-compatible server
Wan AI video generation integration
Distributed as mcp-wan on PyPI

🚀 Use Cases

Enable MCP-based tooling to support Wan AI video generation workflows
Use within developer setups targeting MCP servers for AI video

⚡ Developer Benefits

Python 3.10+ compatibility (per project metadata)
MIT license

⚠️ Limitations

Available source details are limited; no specific MCP tools or capabilities are listed in the provided excerpt.

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

Sign up at AceDataCloud Platform
Go to the API documentation page
Click "Acquire" to get your API token
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:

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

Claude Desktop

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

json

{
  "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):

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):

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

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

json

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

Claude Code

Claude Code supports MCP servers natively:

bash

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:

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):

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:

json

{
  "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:

json

{
  "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:

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):

json

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

cURL Test

bash

# 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:

bash

# 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)

json

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

Docker (Self-Hosting)

bash

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

bash

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

bash

# 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

bash

# 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

bash

# Format code
ruff format .

# Lint code
ruff check .

# Type check
mypy core tools

Build & Publish

bash

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

# Build package
python -m build

# Upload to PyPI
twine upload dist/*

Project Structure

code

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:

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

🛠️ Key Features

🚀 Use Cases

⚡ Developer Benefits

⚠️ Limitations

Topics

WanMCP

Features

Tool Reference

Quick Start

1. Get Your API Token

2. Use the Hosted Server (Recommended)

Claude.ai

Claude Desktop

Cursor / Windsurf

VS Code (Copilot)

JetBrains IDEs

Claude Code

Cline

Amazon Q Developer

Roo Code

Continue.dev

Zed

cURL Test

3. Or Run Locally (Alternative)

Claude Desktop (Local)

Docker (Self-Hosting)

Available Models

Configuration

Environment Variables

Command Line Options

Development

Setup Development Environment

Run Tests

Code Quality

Build & Publish

Project Structure

API Reference

Contributing

Documentation

License

Links

Install

Configuration

Related servers