About
MCP server for Wan AI video generation
Remote endpoints: streamable-http: https://wan.mcp.acedata.cloud/mcp
Security Report
This MCP server is well-structured with proper authentication mechanisms and secure credential handling. The server delegates authentication to AceDataCloud's OAuth 2.0 platform and securely manages API tokens. Permissions appropriately match its purpose as a video generation tool. Minor code quality issues and logging practices are present but do not constitute security vulnerabilities. Supply chain analysis found 7 known vulnerabilities in dependencies (0 critical, 5 high severity). Package verification found 1 issue.
6 files analyzed · 13 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
What You'll Need
Set these up before or after installing:
Environment variable: ACEDATACLOUD_API_TOKEN
How to Install & Connect
Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
Documentation
View on GitHubFrom the project's GitHub README.
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):
{
"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
- Go to Settings → Tools → AI Assistant → Model Context Protocol (MCP)
- Click Add → HTTP
- 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:
- 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
Documentation
License
MIT License - see LICENSE for details.
Links
Made with love by AceDataCloud
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