
Comfyui Core
Core ComfyUI knowledge covering workflow format, node types, pipeline patterns, and MCP...
Install
npx skills add artokun/comfyui-mcp --skill comfyui-core -g -a claude-code -y- Repository
- artokun/comfyui-mcp883
- Category
- AI and agents
- Updated
- 9d ago
- License
- MIT
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- No, instructions only
What it does
Core ComfyUI knowledge covering workflow format, node types, pipeline patterns, and MCP tool usage
ComfyUI Core Knowledge
Workflow JSON Format (API Format)
ComfyUI workflows are JSON objects mapping string node IDs to node definitions:
{
"1": {
"class_type": "CheckpointLoaderSimple",
"inputs": { "ckpt_name": "sd_xl_base_1.0.safetensors" },
"_meta": { "title": "Load Checkpoint" }
},
"2": {
"class_type": "CLIPTextEncode",
"inputs": { "text": "a cat", "clip": ["1", 1] },
"_meta": { "title": "Positive Prompt" }
}
}
Key Rules
- Node IDs are strings of integers (
"1","2", etc.) class_typeis the exact Python class name of the nodeinputscontains both widget values (scalars) and connections (arrays)- Connections use the format
["sourceNodeId", outputIndex], a 2-element array where:- the first element is the string node ID of the source node
- the second element is the integer index into the source node's
outputlist (0-based)
_metais optional and used for display titles only
Connection Examples
"model": ["1", 0] // Connect to node 1's first output (MODEL)
"clip": ["1", 1] // Connect to node 1's second output (CLIP)
"vae": ["1", 2] // Connect to node 1's third output (VAE)
"positive": ["2", 0] // Connect to node 2's first output (CONDITIONING)
"samples": ["5", 0] // Connect to node 5's first output (LATENT)
"images": ["6", 0] // Connect to node 6's first output (IMAGE)

