| name | comfyui-master-control |
| version | 2.0 |
| category | mlops |
| description | Master operational guide for the dual-server ComfyUI setup. Enforces a strict two-layer architecture of MCP Discovery and Direct API Execution. |
ComfyUI Master Control (v2.0)
Architecture Standard: The Two-Layer Protocol
ComfyUI interaction is split into two non-overlapping layers. Mixing these responsibilities is a system failure.
┌─────────────────────────────────────────────────────┐
│ LAYER 1 — MCP (Discovery & Inspection) │
│ Tools: list_workflows, read_workflow, list_models │
│ Source: Local ~/workflows/ + remote /object_info/ │
│ USE ONLY FOR: Finding workflows and inspecting │
│ node structures and model availability. │
└─────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────┐
│ LAYER 2 — Direct API (Execution) │
│ Endpoints: /prompt, /history/{id}, /view │
│ USE ONLY FOR: Submitting jobs, polling status, │
│ and downloading output files. │
└─────────────────────────────────────────────────────┘
⚠️ CRITICAL: MCP tools cannot submit jobs or modify parameters. All generation tasks must be executed via Layer 2 HTTP calls to the remote server.
Server Inventory (Dual RTX 3090 Setup)
Two independent ComfyUI instances running on a single Windows machine.
| Port | GPU Assignment | VRAM | Status/Capability |
|---|
localhost:8188 | RTX 3090 #0 (--cuda-device 0) | 24GB | Primary Image/Video |
localhost:8189 | RTX 3090 #1 (--cuda-device 1) | 24GB | Secondary/Batch |
Probe Availability:
Always verify server health before attempting a job.
curl -s --max-time 3 http://localhost:8188/api/system_stats
curl -s --max-time 3 http://localhost:8189/api/system_stats
Launch Flags (Standard):
--normalvram --reserve-vram 2.0 --fast --fp16-vae --cache-none --use-sage-attention
Layer 1 — MCP Tools (Discovery)
The comfyui-mcp server manages the inspection layer.
list_workflows
Lists all .json files in the local Mac directory ~/workflows/.
- Returns:
{workflow_root, count, workflows: [{name, relative_path...}]}
read_workflow(relative_path)
Loads a workflow JSON and provides the parsed structure.
- Returns:
{relative_path, text, json}
- Note: Use the
json field for all subsequent injection logic.
list_models(kind, recursive, search)
Queries the remote server's /object_info/ to see what is actually loaded in VRAM.
- Kinds:
checkpoints, loras, vae, clip, controlnet
Layer 2 — Direct API (Execution)
All active generation work occurs here via direct HTTP calls.
Submit a Job
Submit the payload as a POST request. Always use a temporary file for payloads to avoid shell argument limits.
curl -s -X POST http://localhost:8188/prompt \
-H "Content-Type: application/json" \
-d @/tmp/payload.json
- Required Payload Format:
{"prompt": {<workflow_dict>}, "client_id": "<uuid>"}
Monitor & Retrieve
- Poll History:
GET http://localhost:8188/history/{prompt_id}
- Wait for the response to contain an
outputs key for your target nodes.
- Download Asset:
GET http://localhost:8188/view?filename=...&subfolder=...&type=output
Standard Workflow Sequence
- PROBE (L2): Check
/api/system_stats to pick an available host.
- DISCOVER (L1): Use
list_workflows and read_workflow to get the target JSON structure.
- INJECT (Local): Deep copy the workflow, modify prompt/seed/resolution nodes in Python.
- SUBMIT (L2): POST the wrapped payload to
/prompt. Capture prompt_id.
- POLL (L2): Periodically check
/history/{prompt_id}.
- DOWNLOAD (L2): Use
/view to save results locally.
Model Inventory (Reference)
| Type | Key Models / Checkpoints |
|---|
| Video | ltx-2.3-22b-dev-fp8, ltx-2.3-22b-distilled-fp8 |
| Z-Image | z_image_bf16, z_image_turbo_bf16 |
| LoRAs | Wan2.2 T2V, ltx-2.3-id-lora, Qwen-Edit-2509 |
Related Skills
| Task | Skill |
|---|
| Submitting Jobs | expert-image-submitter-agent |
| Batch Orchestration | comfyui-local-api-orchestration |
| Video Injection | comfyui-video-direct-injector |
| Workflow Analysis | comfyui-workflow-query-analysis |
