comfyui-api
mckruz/comfyui-expert
Connect to ComfyUI, queue workflows, monitor execution, and retrieve results in online or offline mode.
What is comfyui-api?
This skill provides REST API access to a running ComfyUI instance for executing image generation workflows, polling progress, and downloading outputs. Use it when you need to programmatically control ComfyUI workflows or check server status; supports both online (live API) and offline (JSON export) modes.
- Queue workflows to ComfyUI via REST API and receive prompt IDs
- Poll workflow execution status every 5 seconds until completion
- Retrieve generated images and other outputs from the server
- Upload reference images to ComfyUI's input folder
- Check server status, VRAM availability, and installed models
- Cancel running generations and free VRAM on demand
How to install comfyui-api
npx skills add https://github.com/mckruz/comfyui-expert --skill comfyui-api- A running ComfyUI instance (default: http://127.0.0.1:8188) or ability to export workflows offline
- curl or wget available in PATH for HTTP requests
- ComfyUI server accessible at configured URL with required models and nodes installed
How to use comfyui-api
- 1.Test the connection by calling GET /system_stats to verify ComfyUI is running and check available VRAM
- 2.Use comfyui-inventory skill to discover installed nodes and models, then validate your workflow against them
- 3.Construct a workflow JSON object with numbered nodes, each specifying class_type and inputs with proper node references
- 4.Queue the workflow via POST /prompt with the workflow JSON and receive a prompt_id
- 5.Poll GET /history/{prompt_id} every 5 seconds until the response contains outputs and status.completed is true
- 6.Retrieve output images using GET /view with the filename, subfolder, and type from the outputs
- 7.If ComfyUI is unavailable, generate and save the workflow JSON to projects/{project}/workflows/{name}.json for manual loading
Use cases
- Generate images programmatically by queuing Flux or other model workflows to a local ComfyUI instance
- Monitor long-running video generation tasks (15-30 minutes) and retrieve results when complete
- Validate that required models and custom nodes are installed before attempting workflow execution
- Upload reference images and control generation parameters dynamically from code
- Switch to offline mode to export workflow JSON when ComfyUI server is not running
- AI agents executing image or video generation workflows
- Developers building automation around ComfyUI
- Users running ComfyUI locally and needing programmatic control
- Teams managing ComfyUI instances with custom nodes and models
comfyui-api FAQ
Most image generations complete in seconds to minutes. Video generation with Wan 14B can take 15-30 minutes. The skill warns after 10 minutes of polling; continue waiting for longer tasks.
Validate the workflow JSON structure: ensure all node IDs are strings, inputs reference other nodes as ["node_id", output_index], and all class_types match installed nodes. Use comfyui-inventory to verify node availability.
Yes. Switch to offline mode: generate the workflow JSON following ComfyUI's format and save it to projects/{project}/workflows/{name}.json. Instruct the user to drag-drop it into ComfyUI manually.
Use POST /upload/image with multipart form data: image file, subfolder (e.g., 'input'), and type ('input'). Then reference the uploaded filename in your workflow's LoadImage node.
The workflow will fail with a 500 error. Call POST /free with {"unload_models": true} to free VRAM, then retry the workflow or suggest the user reduce batch size or use a smaller model.
Full instructions (SKILL.md)
Source of truth, from mckruz/comfyui-expert.
name: comfyui-api description: Connect to a running ComfyUI instance, queue workflows, monitor execution, and retrieve results. Supports both online (REST API) and offline (JSON export) modes. Use when executing ComfyUI workflows or checking server status. user-invocable: true metadata: {"openclaw":{"emoji":"🔌","os":["darwin","linux","win32"],"requires":{"anyBins":["curl","wget"]},"primaryEnv":"COMFYUI_URL"}}
ComfyUI API Skill
Connect to ComfyUI's REST API to execute workflows, monitor progress, and retrieve outputs.
Configuration
- Default URL:
http://127.0.0.1:8188 - Custom URL: Set in project manifest or pass as parameter
- Timeout: 30s for API calls, no timeout for generation polling
Two Modes
Online Mode (ComfyUI Running)
Full API access. Preferred mode for interactive work.
- Test connection:
GET /system_stats - Discover capabilities: Use
comfyui-inventoryskill - Queue workflow:
POST /prompt - Poll for results:
GET /history/{prompt_id}every 5 seconds - Retrieve outputs:
GET /view?filename=...
Offline Mode (No Server)
Export workflow JSON for manual loading in ComfyUI.
- Generate workflow JSON following ComfyUI's format
- Save to
projects/{project}/workflows/{name}.json - Instruct user to drag-drop into ComfyUI
API Operations
Check Server Status
curl http://127.0.0.1:8188/system_stats
Response fields:
system.os: Operating systemsystem.comfyui_version: Version stringdevices[0].name: GPU namedevices[0].vram_total: Total VRAM bytesdevices[0].vram_free: Free VRAM bytes
Queue a Workflow
curl -X POST http://127.0.0.1:8188/prompt \
-H "Content-Type: application/json" \
-d '{"prompt": WORKFLOW_JSON, "client_id": "video-agent"}'
WORKFLOW_JSON format:
{
"1": {
"class_type": "LoadCheckpoint",
"inputs": {
"ckpt_name": "flux1-dev.safetensors"
}
},
"2": {
"class_type": "CLIPTextEncode",
"inputs": {
"text": "photorealistic portrait...",
"clip": ["1", 1]
}
}
}
Each node is keyed by a string ID. Inputs reference other nodes as ["{node_id}", {output_index}].
Response:
{"prompt_id": "abc-123-def", "number": 1}
Poll for Completion
curl http://127.0.0.1:8188/history/abc-123-def
Incomplete: Returns {} (empty object)
Complete: Returns execution data with outputs:
{
"abc-123-def": {
"outputs": {
"9": {
"images": [{"filename": "ComfyUI_00001.png", "subfolder": "", "type": "output"}]
}
},
"status": {"completed": true}
}
}
Retrieve Output Image
curl "http://127.0.0.1:8188/view?filename=ComfyUI_00001.png&subfolder=&type=output" -o output.png
Upload Reference Image
curl -X POST http://127.0.0.1:8188/upload/image \
-F "image=@reference.png" \
-F "subfolder=input" \
-F "type=input"
Cancel Current Generation
curl -X POST http://127.0.0.1:8188/interrupt
Free VRAM
curl -X POST http://127.0.0.1:8188/free \
-H "Content-Type: application/json" \
-d '{"unload_models": true}'
Polling Strategy
ComfyUI doesn't support WebSocket in CLI context. Use REST polling:
- Queue workflow via
POST /prompt→ getprompt_id - Poll
GET /history/{prompt_id}every 5 seconds - On empty response: generation in progress, continue polling
- On populated response: check
status.completed - If
completed: true, extract outputs - If error in status, route to
comfyui-troubleshooter
Timeout: Warn user after 10 minutes of polling. Video generation (Wan 14B) can take 15-30 minutes.
Workflow Validation
Before queuing any workflow:
- Read
state/inventory.json(viacomfyui-inventory) - For each node in workflow: verify
class_typeexists in installed nodes - For each model reference: verify file exists in installed models
- Flag missing items with:
- Node: suggest
ComfyUI-Managerinstall command - Model: provide download link from
references/models.md - Version mismatch: suggest update
- Node: suggest
Error Handling
| Error | Cause | Action |
|---|---|---|
| Connection refused | ComfyUI not running | Switch to offline mode, save JSON |
| 400 Bad Request | Invalid workflow JSON | Validate node connections |
| 500 Internal Error | ComfyUI crash | Suggest restart, check logs |
| Timeout (no response) | Server overloaded | Wait and retry once |
Reference
Full API documentation: foundation/api-quick-ref.md
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