workflows

name	workflows
description	Knowledge about ComfyUI workflow API format, node connections, and common patterns. Use when helping users build, modify, or understand workflows.

ComfyUI Workflow Building Guide

API Format

ComfyUI workflows use a JSON format where each node is a key-value pair:

{
  "1": {
    "class_type": "KSampler",
    "inputs": {
      "seed": 42,
      "steps": 20,
      "cfg": 7.0,
      "sampler_name": "euler",
      "scheduler": "normal",
      "denoise": 1.0,
      "model": ["2", 0],
      "positive": ["3", 0],
      "negative": ["4", 0],
      "latent_image": ["5", 0]
    }
  }
}

• Keys are string node IDs (e.g., "1", "2")
• class_type is the ComfyUI node type name
• inputs contains parameters and connections
• Connections use the format ["source_node_id", output_index]

Common Node Chains

txt2img (text to image)

CheckpointLoaderSimple -> CLIPTextEncode (positive) -> KSampler -> VAEDecode -> SaveImage

img2img (image to image)

LoadImage -> VAEEncode -> KSampler (with denoise < 1.0) -> VAEDecode -> SaveImage

ControlNet

LoadImage -> ControlNetLoader + ControlNetApply -> feed into KSampler positive conditioning

LoRA Stacking

CheckpointLoaderSimple -> LoraLoader (chain multiple) -> KSampler

Key Nodes Reference

Node	Purpose	Key Inputs
CheckpointLoaderSimple	Load a model checkpoint	ckpt_name
CLIPTextEncode	Encode text prompt	text, clip
KSampler	Run diffusion sampling	model, positive, negative, latent_image, steps, cfg, seed
VAEDecode	Decode latent to image	samples, vae
VAEEncode	Encode image to latent	pixels, vae
SaveImage	Save output image	images, filename_prefix
LoadImage	Load input image	image (filename)
LoraLoader	Apply LoRA weights	model, clip, lora_name, strength_model, strength_clip
ControlNetLoader	Load ControlNet model	control_net_name
ControlNetApply	Apply ControlNet	conditioning, control_net, image, strength

Using the Workflow Tools

Quick decision guide — pick the tool by what you need to do:

Goal	Tool
Build a new workflow from scratch	comfyui_create_workflow
Modify an existing workflow	comfyui_modify_workflow
Understand a workflow (human-readable text or Mermaid)	comfyui_summarize_workflow
Understand a workflow (machine-readable dict)	comfyui_analyze_workflow
Check a workflow for errors before running	comfyui_validate_workflow
Execute a workflow	comfyui_run_workflow

1. comfyui_create_workflow — Start from a built-in template. Accepted template names are listed in the tool's docstring: txt2img, img2img, upscale, inpaint, txt2vid_animatediff, txt2vid_wan, controlnet_canny, controlnet_depth, controlnet_openpose, ip_adapter, lora_stack, face_restore, flux_txt2img, sdxl_txt2img. The params argument defaults to "", which applies the predefined settings for the selected template (e.g., default dimensions, steps, and cfg values baked into that template); pass a JSON string when you want overrides. (Note: comfyui_list_workflows returns server-side /workflow_templates from front-end packages — a different set, not these MCP-built-in templates.)
2. comfyui_modify_workflow — Add/remove nodes, change connections, update parameters on an existing workflow. Operations: add_node, remove_node, set_input, connect, disconnect. The docstring spells out each op's exact field shape. The call is atomic — if any operation fails, the call raises and the input workflow is unmodified.
3. comfyui_validate_workflow — Returns {valid, errors, warnings, node_count, pipeline}. errors (list[str]) are blocking; warnings (list[str]) are non-blocking concerns like missing model files or suspicious inputs.
4. comfyui_summarize_workflow — Human-readable overview. Pass output_format="text" (default) or "mermaid" for diagram markup.
5. comfyui_analyze_workflow — Returns the analysis as a structured dict (node_count, class_types, flow, models, parameters, pipeline, prompt_nodes, negative_nodes). Use this when you want to read fields like pipeline programmatically; use comfyui_summarize_workflow for the human-readable rendering.
6. comfyui_run_workflow — Submit a workflow for execution. Use wait=True to block until done. The response is always a dict envelope: {status, prompt_id, outputs, elapsed_seconds, warnings?} where status is one of submitted / completed / interrupted / error / timeout. With wait=False you get just {status: "submitted", prompt_id, warnings?} — poll comfyui_get_progress or comfyui_get_job to follow up.

Tips

• Always validate a workflow before running it.
• Use comfyui_list_nodes to check what node types are available on the connected ComfyUI instance.
• Use comfyui_get_node_info to get detailed input/output specs for a specific node type.
• Node IDs must be unique strings. When adding nodes, pick IDs that don't conflict with existing ones.
• The seed parameter controls reproducibility. Use a fixed seed for consistent results, or -1 for random.