Wan2GP MCP Server

A Model Context Protocol (MCP) server that provides AI assistants (like Claude Desktop) with access to Wan2GP video generation capabilities.

Overview

This MCP server communicates with a running Wan2GP Gradio instance to generate videos from text prompts and images. It's designed to work with Wan2GP installations via StabilityMatrix or standalone setups.

Related MCP server: Vidu MCP

Features

• Text-to-Video: Generate videos from text descriptions

• Image-to-Video: Animate static images with text prompts

• Queue Management: View and manage generation queue

• Model Listing: Discover available video generation models

• LoRA Support: List available LoRA adapters

• Health Monitoring: Check Wan2GP server status

Architecture

Claude Desktop (MCP Client)
    ↓ stdio (JSON-RPC 2.0)
Wan2GP MCP Server
    ↓ HTTP requests
Wan2GP Gradio Server (localhost:7860)

Prerequisites

1. Wan2GP Server: A running Wan2GP Gradio instance

   • Install via StabilityMatrix or manually

   • Start the Gradio server: python wgp.py --server-name 0.0.0.0 --server-port 7860

2. Python 3.10+: Required for the MCP server

3. Claude Desktop (optional): For MCP integration

Installation

1. Clone or Download

cd /path/to/your/projects
git clone <this-repo> wan2gp-mcp-server
cd wan2gp-mcp-server

2. Install Dependencies

pip install -r requirements.txt

3. Configure Server URL

Edit config.json to match your Wan2GP server URL:

{
  "wan2gp_url": "http://localhost:7860",
  "timeout": 300,
  "max_concurrent_tasks": 3,
  "default_model": "wan",
  "default_resolution": "1280x720",
  "output_directory": "./output"
}

Or set via environment variable:

export WAN2GP_URL="http://localhost:7860"
export WAN2GP_TIMEOUT="300"

Usage

Standalone Testing

Test the MCP server directly:

python wan2gp_mcp_server.py

In another terminal, test with an MCP client or inspect the logs.

Claude Desktop Integration

1. Add to Claude Desktop Config

   Locate Claude Desktop's config file:

   • Windows: %APPDATA%\Claude\claude_desktop_config.json

   • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

   • Linux: ~/.config/Claude/claude_desktop_config.json

2. Merge the Configuration

   Add the wan2gp server to the mcpServers section:

   {
     "mcpServers": {
       "wan2gp": {
         "command": "python",
         "args": [
           "/absolute/path/to/wan2gp-mcp-server/wan2gp_mcp_server.py"
         ],
         "env": {
           "WAN2GP_URL": "http://localhost:7860",
           "WAN2GP_TIMEOUT": "300",
           "LOG_LEVEL": "INFO"
         }
       }
     }
   }

   Important: Use absolute paths in the args section.

3. Restart Claude Desktop

   Claude will load the MCP server on startup.

4. Use in Claude

   Now you can ask Claude to generate videos:

   Generate a 5-second video of a cat walking through a sunny garden

   Claude will use the MCP server to submit the generation task.

MCP Tools

The server provides the following tools:

generate_text_to_video

Generate a video from text description.

Parameters:

• prompt (required): Text description of the video

• negative_prompt: Things to avoid in the video

• resolution: Video resolution (e.g., "1280x720", "1920x1080")

• video_length: Number of frames (49 ≈ 2 seconds at 24fps)

• num_inference_steps: Number of denoising steps (20-50 recommended)

• guidance_scale: How strongly to follow the prompt (1-20)

• seed: Random seed (-1 for random)

• model_type: Model to use (wan, hunyuan, ltx, etc.)

• output_filename: Custom output filename

Example:

generate_text_to_video(
    prompt="A cat walking through a sunny garden, slow motion",
    resolution="1280x720",
    num_inference_steps=25,
    guidance_scale=7.5
)

generate_image_to_video

Animate a static image based on a text prompt.

Parameters:

• image_path (required): Path to the input image

• prompt (required): How the image should animate/move

• negative_prompt: Things to avoid in the video

• motion_scale: How much motion to generate (0.5-2.0)

• video_length: Number of frames

• num_inference_steps: Number of denoising steps

• guidance_scale: How strongly to follow the prompt

• seed: Random seed (-1 for random)

• model_type: Model to use

Example:

generate_image_to_video(
    image_path="/path/to/image.jpg",
    prompt="Camera slowly zooms in, clouds drift across the sky",
    motion_scale=1.2
)

health_check

Check if Wan2GP server is running and accessible.

Returns:

{
  "status": "healthy",
  "url": "http://localhost:7860",
  "version": "10.951"
}

list_models

List all available video generation models.

Returns:

[
  {
    "name": "Wan2.1 T2V",
    "id": "t2v_2_2",
    "type": "text_to_video",
    "resolution": "480p-8K",
    "vram_requirement": "16GB+"
  }
]

list_loras

List available LoRA adapters.

get_queue

Get the current generation queue.

cancel_task

Cancel a queued generation task.

MCP Resources

The server provides the following resources:

• wan2gp://models - List available models (JSON)

• wan2gp://loras - List available LoRAs (JSON)

• wan2gp://queue - Current generation queue (JSON)

• wan2gp://health - Server health status (JSON)

Troubleshooting

"Cannot connect to Wan2GP server"

• Ensure Wan2GP Gradio server is running

• Check the URL in config.json matches your server

• Verify the server port (default: 7860)

"Flash-Attention version conflict"

This is a Wan2GP environment issue, not related to the MCP server. Ensure Wan2GP's dependencies are correctly installed:

# In Wan2GP environment
pip install flash-attn==2.7.4

Claude Desktop doesn't show MCP tools

1. Check Claude Desktop logs: Help > Developer > Show Logs

2. Verify absolute paths in config

3. Ensure Python is in system PATH

4. Test the server manually: python wan2gp_mcp_server.py

Development

Running Tests

# Test client
python tests/test_client.py

# Test with MCP inspector
npx @modelcontextprotocol/inspector python wan2gp_mcp_server.py

Adding New Tools

Edit wan2gp_mcp_server.py and add a new tool using the @mcp.tool decorator:

@mcp.tool
async def my_new_tool(param: str) -> str:
    """Tool description."""
    client = await get_client()
    # ... implementation
    return "result"

Configuration Reference

config.json

Environment Variables

License

This MCP server is provided as-is for use with Wan2GP.

Credits

• Wan2GP - Video generation models and Gradio interface

• FastMCP - MCP server framework

• Anthropic - Model Context Protocol