comfyui-workflow-query-analysis

name	comfyui-workflow-query-analysis
version	1.0
description	Query remote ComfyUI servers and analyze workflow files using direct API access and local parsing.

ComfyUI Workflow Query & Analysis (Direct API Edition)

A comprehensive guide for querying remote ComfyUI servers and analyzing workflow files locally.

System Stats API

Get Server Information

curl http://localhost:8188/api/system_stats | python3 -m json.tool
curl http://localhost:8189/api/system_stats | python3 -m json.tool

⚠️ Must use /api/system_stats — not /system_stats (returns nothing on ComfyUI 0.18.2+).

Response includes:

• OS (win32), Python version, PyTorch version
• GPU device info (name, VRAM total/free)

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Workflow File Formats — CRITICAL DISTINCTION

ComfyUI has two different JSON formats. Using the wrong parser for the wrong format is a common failure.

Format 1: API Prompt Format (used for submission via /prompt)

Flat dictionary keyed by node ID string. This is what you inject into and POST.

{
  "6": { "class_type": "CLIPTextEncode", "inputs": { "text": "...", "clip": ["4", 1] } },
  "8": { "class_type": "EmptyLatentImage", "inputs": { "width": 1024, "height": 1024 } }
}

Format 2: UI Save Format (exported from ComfyUI browser interface)

Nested structure with a nodes array and a definitions.subgraphs wrapper (used in newer ComfyUI versions) or a top-level nodes array (older versions). Cannot be submitted directly to /prompt — must be converted to Format 1 first.

{
  "id": "workflow-id",
  "definitions": {
    "subgraphs": [
      { "nodes": [...], "links": [...] }
    ]
  }
}

Rule: Workflows in ~/ComfyUI/workflows/ saved from the UI are Format 2. Workflows used for API injection must be Format 1. When in doubt, check whether the top-level keys are numeric strings — if yes, it's Format 1.

Python Parser for UI Format (Format 2)

import json
from pathlib import Path

def analyze_workflow(wf_file):
    with open(wf_file) as f:
        d = json.loads(f.read())
    
    # Get nodes from subgraphs (not flat 'nodes' field)
    defs = d.get('definitions', {})
    subgraphs = defs.get('subgraphs', [])
    all_nodes = []
    
    for sg in subgraphs:
        if isinstance(sg, dict):
            nodes_list = sg.get('nodes', [])
            if isinstance(nodes_list, list):
                all_nodes.extend(nodes_list)
    
    node_types = [n.get('class_type', 'unknown') for n in all_nodes]
    return len(all_nodes), node_types

Python Parser for API Format (Format 1)

def analyze_api_workflow(wf_file):
    with open(wf_file) as f:
        d = json.load(f)
    for node_id, node in d.items():
        print(f"Node {node_id}: {node.get('class_type')} — inputs: {list(node.get('inputs', {}).keys())}")

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Troubleshooting Tips

Empty Subgraphs (0 nodes)

Some workflows may have empty subgraphs - these are typically:

• Template files awaiting configuration
• Incomplete imports

Check: Verify the workflow was fully saved by opening in ComfyUI and re-exporting.

MCP Layer

For listing and reading workflow files, use the MCP layer (list_workflows, read_workflow) — those tools read local ~/workflows/ files without needing the server up. This skill handles the analysis and direct API query layer. See comfyui-master-control for the full two-layer architecture.

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Verification Checklist

• Server responds to /api/system_stats
• Workflow files parse without errors
• Node count matches visual inspection in ComfyUI
• Subgraph structure is properly nested