ComfyUI Custom Node Development

This skill helps you create custom ComfyUI nodes from Python code.

Quick Template

class MyNode: @classmethod def INPUT_TYPES(cls): return { "required": { "image": ("IMAGE",), "value": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0}), }, "optional": { "mask": ("MASK",), } }

RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("output",)
FUNCTION = "execute"
CATEGORY = "Custom/MyNodes"

def execute(self, image, value, mask=None):
    result = image * value
    return (result,)

NODE_CLASS_MAPPINGS = {"MyNode": MyNode} NODE_DISPLAY_NAME_MAPPINGS = {"MyNode": "My Node"}

Converting Python to Node

When you have Python code to wrap:

Step 1: Identify inputs and outputs

Original function

def apply_blur(image, radius=5): from PIL import ImageFilter return image.filter(ImageFilter.GaussianBlur(radius))

Step 2: Map types

Python Type ComfyUI Type Conversion

PIL Image IMAGE torch.from_numpy(np.array(pil) / 255.0)

numpy array IMAGE torch.from_numpy(arr.astype(np.float32))

cv2 BGR IMAGE torch.from_numpy(cv2.cvtColor(img, cv2.COLOR_BGR2RGB) / 255.0)

float 0-255 IMAGE Divide by 255.0

Single image Batch tensor.unsqueeze(0)

Step 3: Handle batch dimension

ComfyUI images are [B,H,W,C]

• always process all batch items:

def execute(self, image, radius): batch_results = [] for i in range(image.shape[0]): # Convert to PIL img_np = (image[i].cpu().numpy() * 255).astype(np.uint8) pil_img = Image.fromarray(img_np)

    # Your processing
    result = pil_img.filter(ImageFilter.GaussianBlur(radius))

    # Convert back
    result_np = np.array(result).astype(np.float32) / 255.0
    batch_results.append(torch.from_numpy(result_np))

return (torch.stack(batch_results),)

Common Input Types

Type Shape/Format Widget Options

IMAGE [B,H,W,C] float 0-1

MASK [H,W] or [B,H,W] float 0-1

LATENT {"samples": [B,C,H,W]}

MODEL ModelPatcher

CLIP CLIP encoder

VAE VAE model

CONDITIONING [(cond, pooled), ...]

INT integer default, min, max, step

FLOAT float default, min, max, step, display

STRING str default, multiline

BOOLEAN bool default

COMBO str List of options as type

Checklist

• INPUT_TYPES is a @classmethod

• Return value is a tuple: return (result,)

• Handle batch dimension [B,H,W,C]

• Add to NODE_CLASS_MAPPINGS

• Category uses / for submenus

References

• NODE_TEMPLATE.md - Full template with V3 schema

• OFFICIAL_DOCS.md - Official ComfyUI documentation

• PURZ_EXAMPLES.md - Example nodes and workflows

Finding Similar Nodes

Use the MCP tools to find existing nodes for reference:

comfy_search("blur") → Find blur implementations comfy_spec("GaussianBlur") → See how inputs are defined