Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@ComfyUI MCP Servergenerate a cinematic image of a futuristic city at sunset"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
What is this?
ComfyUI MCP Server connects Claude Desktop (or Claude Code) to your local ComfyUI instance. Once set up, you can ask Claude to generate images and it will run them through Stable Diffusion, SDXL, or whatever checkpoint models you have installed -- no copy-pasting prompts between apps.
It works over MCP (Model Context Protocol), which means Claude treats your ComfyUI setup as a native tool.
Example conversation:
You: Generate a watercolor painting of a coastal village at sunrise
Claude: I'll generate that using your SDXL model.
[calls generate_image -> ComfyUI runs the workflow -> returns result]
Done -- saved as ComfyUI-MCP_00042.png (14.2s)How it works
Claude Desktop / Claude Code
|
v
MCP Server (stdio)
|
v
ComfyUI REST API (localhost:8188)
|
v
Your GPU -> Stable Diffusion / SDXL / etc.The server translates Claude's tool calls into ComfyUI workflow submissions, polls for completion, and returns the results.
Prerequisites
Python 3.11+
ComfyUI running locally (default:
http://127.0.0.1:8188)At least one checkpoint model installed in ComfyUI
Installation
git clone https://github.com/MatthewSnow2/comfyui-mcp.git
cd comfyui-mcp
python -m venv .venv
source .venv/bin/activate # Linux/macOS
# .venv\Scripts\activate # Windows
pip install -e ".[dev]"Setup
1. Configure environment
Copy .env.example to .env and adjust if needed:
cp .env.example .envVariable | Default | What it does |
|
| Where your ComfyUI is running |
|
| Where generated images get saved |
|
| Which checkpoint to use by default |
|
| Sampling steps |
|
| Image width (px) |
|
| Image height (px) |
|
| CFG scale |
2. Add to Claude Desktop
Add this block to your claude_desktop_config.json:
{
"mcpServers": {
"comfyui": {
"command": "/path/to/comfyui-mcp/.venv/bin/comfyui-mcp",
"env": {
"COMFYUI_URL": "http://127.0.0.1:8188",
"COMFYUI_DEFAULT_MODEL": "sd_xl_base_1.0.safetensors"
}
}
}
}Replace /path/to/comfyui-mcp with your actual install path.
Config file locations:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.jsonLinux:
~/.config/Claude/claude_desktop_config.json
3. Restart Claude Desktop
Restart the app. You should see "comfyui" listed in the MCP tools dropdown.
What you can do
Generate images
Ask Claude to generate an image from any text prompt. It handles prompt engineering, model selection, and parameter tuning.
Parameter | Type | Default | Description |
| string | (required) | What you want to see |
| string |
| What to avoid |
| string | config default | Checkpoint model name |
| int |
| Width in pixels |
| int |
| Height in pixels |
| int |
| Sampling steps (more = slower but often better) |
| float |
| How closely to follow the prompt |
| int |
| Random seed (-1 = random each time) |
List your models
Ask "what models do I have?" and Claude will show every checkpoint installed in your ComfyUI.
Check queue status
Ask "what's in the queue?" to see how many jobs are pending, running, or completed.
Look up past generations
Give Claude a prompt ID from a previous generation and it will pull up the details.
Real usage examples
You: What models do I have?
Claude: You have 3 checkpoints:
- sd_xl_base_1.0.safetensors
- dreamshaper_8.safetensors
- realisticVision_v51.safetensors
You: Generate a cyberpunk street scene using dreamshaper at 512x768
Claude: [runs generation with dreamshaper_8, 512x768]
Done -- ComfyUI-MCP_00043.png (8.3s)
You: Same scene but make it daytime and use realisticVision
Claude: [runs generation with realisticVision_v51, same dimensions]
Done -- ComfyUI-MCP_00044.png (9.1s)Development
Run tests
pytestLint and type check
ruff check src/ tests/
mypy src/Run the server directly
python -m src.serverProject structure
comfyui-mcp/
src/
server.py # MCP server entry point
comfyui_client.py # HTTP client for ComfyUI API
config.py # Settings via pydantic-settings
models.py # Pydantic data models
workflows.py # ComfyUI workflow templates
tests/ # pytest suite
pyproject.toml
README.mdBuilt with
MCP SDK -- Model Context Protocol
ComfyUI -- Node-based Stable Diffusion UI
Pydantic -- Data validation
httpx -- Async HTTP client
License
MIT
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