MCPInstall

comfyui-api

by mckruzBackend & APIs

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.

Installs
2K
Last 24h
+8
Trending rank
#9788
Security
Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/mckruz/comfyui-expert --skill comfyui-api
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads comfyui-api automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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.

  1. Test connection: GET /system_stats
  2. Discover capabilities: Use comfyui-inventory skill
  3. Queue workflow: POST /prompt
  4. Poll for results: GET /history/{prompt_id} every 5 seconds
  5. Retrieve outputs: GET /view?filename=...

Offline Mode (No Server)

Export workflow JSON for manual loading in ComfyUI.

  1. Generate workflow JSON following ComfyUI's format
  2. Save to projects/{project}/workflows/{name}.json
  3. 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 system
  • system.comfyui_version: Version string
  • devices[0].name: GPU name
  • devices[0].vram_total: Total VRAM bytes
  • devices[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:

  1. Queue workflow via POST /prompt → get prompt_id
  2. Poll GET /history/{prompt_id} every 5 seconds
  3. On empty response: generation in progress, continue polling
  4. On populated response: check status.completed
  5. If completed: true, extract outputs
  6. 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:

  1. Read state/inventory.json (via comfyui-inventory)
  2. For each node in workflow: verify class_type exists in installed nodes
  3. For each model reference: verify file exists in installed models
  4. Flag missing items with:
    • Node: suggest ComfyUI-Manager install command
    • Model: provide download link from references/models.md
    • Version mismatch: suggest update

Error Handling

ErrorCauseAction
Connection refusedComfyUI not runningSwitch to offline mode, save JSON
400 Bad RequestInvalid workflow JSONValidate node connections
500 Internal ErrorComfyUI crashSuggest restart, check logs
Timeout (no response)Server overloadedWait and retry once

Reference

Full API documentation: foundation/api-quick-ref.md

FAQ

What does the comfyui-api skill do?

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.

How do I install comfyui-api?

Run npx skills add https://github.com/mckruz/comfyui-expert --skill comfyui-api in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/comfyui-api/ (personal) or .claude/skills/comfyui-api/ (project).

Which AI agents can use comfyui-api?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is comfyui-api safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains comfyui-api?

It is published by mckruz in mckruz/comfyui-expert. It has 1,970 recorded installs.

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