Getting Started

Overview

comfy-cli is a command line tool that streamlines installation and management of Comfy, and gives you scriptable, single-command access to the entire ComfyUI ecosystem locally or in the cloud. It serves three primary functions:

Manage a local ComfyUI installation — install, launch, update, snapshot, and bisect ComfyUI and custom nodes.
Access hosted partner nodes — generate images, video, audio, and 3D from providers including Seedance, Nano Banana (Gemini), Grok, Flux, Ideogram, DALL·E, Recraft, Stability, Kling, Luma, Runway, Pika, Vidu, Hailuo, Moonvalley, and others with single commands.
Run full workflows on Comfy Cloud — submit workflow graphs, browse the curated template gallery, slot-edit workflows, and watch jobs to completion without a local GPU.

Two surfaces, one CLI. Every command auto-detects where to run. If you are signed in to Comfy Cloud, commands route to cloud; otherwise they run against your local server. Override per call with --where local|cloud, the COMFY_WHERE env var, or persist it with comfy set-default --where cloud.

Install CLI

pip install comfy-cli

brew tap Comfy-Org/comfy-cli
brew install comfy-org/comfy-cli/comfy-cli

To get shell completion hints:

comfy --install-completion

Quick Setup (Recommended)

New in recent versions: a single interactive wizard that handles routing, auth, and agent skills in one step.

comfy setup

It walks you through choosing a routing target (local or cloud), signing in through your browser (OAuth), picking a project directory, and optionally installing the agent skills. This is the recommended path. It opens the browser sign-in for you, with no keys to copy.

comfy setup --where cloud

Non-interactive (CI only). Browser OAuth needs an interactive session. For CI, devcontainers, and scripted installs where no browser is available, pass an API key instead:

comfy setup --where cloud --api-key comfyui-... --non-interactive

Flag	Purpose
`--where local\|cloud`	Routing target; skips the prompt
`--project-dir`	Directory for workflows, inputs, and outputs
`--api-key`	(Optional) Comfy Cloud API key for headless/CI; implies `--where cloud`
`-y, --non-interactive`	No prompts. Drive everything from flags
`--skip-skills`	Do not install agent skills
`--skip-verify`	Skip the connectivity check

Install ComfyUI (Local)

Create a virtual environment with any Python version greater than 3.9.

conda create -n comfy-env python=3.11
conda activate comfy-env

python3 -m venv comfy-env
source comfy-env/bin/activate

Install ComfyUI

comfy install

You still need to install CUDA, or ROCm depending on your GPU.

Run ComfyUI (Local)

comfy launch

Run in the background and stop it later:

comfy launch --background
comfy stop

Check which workspace is selected and what is installed:

comfy which
comfy env

Comfy Cloud

Run workflows and partner nodes on Comfy’s hosted GPUs. No local install required.

comfy cloud login          # browser OAuth + PKCE
comfy cloud whoami         # show sign-in status, auth method, base URL
comfy cloud logout         # clear the local session

Once signed in, commands auto-route to cloud. Browser OAuth is the recommended path. No keys to manage, and the CLI handles token refresh for you. To point at a custom environment (for example a PR preview) before signing in:

comfy cloud set-base-url https://my-preview.comfy.org

API key is optional. You only need an API key for headless or CI use where a browser sign-in is not possible. It is a fallback, not the default:

export COMFY_API_KEY=comfyui-...   # or pass --api-key per call

Session lifetime. Cloud session tokens are short-lived (~1h). The CLI auto-refreshes them on demand. If a command reports cloud_unauthorized, run comfy cloud login again.

Generate with Partner Nodes

comfy generate is in beta. Flag names, model aliases, and output formats may change. The underlying partner endpoints are stable. File feedback on the comfy-cli GitHub repo.

The fastest way to call Comfy’s partner nodes from a terminal or script. It hits the same hosted endpoints as ComfyUI workflows, but as single CLI calls. Ideal for batch jobs, quick experiments, and automation where a full ComfyUI graph is unnecessary.

Prerequisites

An active Comfy Cloud session via comfy cloud login (browser OAuth), or a Comfy API key (--api-key / COMFY_API_KEY) for headless or CI use
Credits on your account
Optional: Browse partner nodes and per-call pricing

First generation

comfy generate flux-pro \
    --prompt "a cat on the moon, cinematic lighting" \
    --width 1024 --height 1024 \
    --download cat.png

The CLI uploads local files, submits the job, polls for completion, and saves results.

Discover a model’s real parameters first. Flag names differ per model (for example flux-ultra takes --width/--height; seedance takes --ratio/--resolution/--duration). Always check before scripting:

comfy generate schema flux-ultra

Common models

Nano Banana (Google Gemini): text-to-image and editing:

comfy generate nano-banana \
    --prompt "a watercolor of a sleeping fox" \
    --download fox.png

# Image editing:
comfy generate nano-banana \
    --prompt "add a top hat" \
    --image ./cat.png \
    --download edited.png

# Specify a model variant:
comfy generate nano-banana \
    --prompt "neon city skyline" \
    --model gemini-3-pro-image-preview \
    --download city.png

Flux 1.1 Pro Ultra: high-resolution text-to-image:

comfy generate flux-ultra \
    --prompt "a purple Victorian house in San Francisco, golden hour" \
    --width 896 --height 1152 --seed 11 \
    --download house.png

Seedance (ByteDance): text-to-video and image-to-video, up to 1080p / 12s:

# Text-to-video:
comfy generate seedance \
    --prompt "a hummingbird hovering over a flower" \
    --resolution 1080p --duration 5 \
    --download hummingbird.mp4

# Image-to-video (animate a local image, auto-uploaded):
comfy generate seedance \
    --model seedance-1-0-pro-250528 \
    --image ./painting.png \
    --ratio 3:4 --resolution 1080p --duration 5 \
    --prompt "the painting gently comes alive, a soft breeze stirs the trees" \
    --download animated.mp4

Grok (xAI): images and video:

comfy generate grok --prompt "a cyberpunk street market at night" --download street.png
comfy generate grok-edit --prompt "swap the umbrella for a parasol" --image ./photo.jpg --download out.png
comfy generate grok-video --prompt "a paper plane gliding through a cathedral" --download flight.mp4

Discover models

comfy generate list                            # all models
comfy generate list --category text-to-video   # filter by category
comfy generate list --partner kling            # filter by partner
comfy generate schema flux-kontext             # view a model's parameters

Image editing with references

Pass local file paths. The CLI uploads via Comfy’s storage endpoint or base64-encodes as needed:

comfy generate nano-banana \
    --prompt "add a top hat" \
    --image ./cat.png \
    --download edited.png

comfy generate flux-kontext \
    --prompt "add a top hat and a monocle" \
    --input_image ./photo.jpg \
    --download out.png

comfy generate ideogram-edit \
    --image cat.png --mask mask.png \
    --prompt "add sunglasses" \
    --rendering_speed TURBO \
    --download edited.png

To upload once and reuse across calls:

comfy generate upload ./photo.jpg     # prints a signed URL

Uploaded reference assets auto-delete after 24 hours. They are stored in Comfy-managed GCS with signed URLs. For long-running pipelines, re-upload before each job. See the reference for details.

Video generation (async jobs)

Video jobs are async. The CLI blocks and polls by default:

comfy generate seedance \
    --prompt "a hummingbird hovering over a flower" \
    --resolution 1080p --duration 5 \
    --download hummingbird.mp4

comfy generate kling \
    --prompt "a paper boat drifting on a river at dusk" \
    --duration 5 \
    --download boat.mp4

Return immediately with --async, then resume later:

comfy generate luma --prompt "neon koi swimming through clouds" --aspect_ratio 16:9 --async
# prints a job id; resume with:
comfy generate resume luma <job_id> --download out.mp4

JSON output for scripts

Emit raw API responses for pipeline integration:

comfy generate dalle --prompt "a watercolor whale" --json | jq '.data[0].url'

See the reference for the full list of commands, flags, and model aliases.

Run Workflows (`comfy run`)

Beyond single partner calls, comfy run submits a complete ComfyUI workflow graph. It accepts both API-format and exported UI-format JSON (UI workflows are converted to API format client-side), and routes to local or cloud like every other command. It is async by default. It returns a prompt_id in milliseconds while a background watcher tracks progress. Pass --wait to block instead.

# Submit; returns immediately with a prompt_id
RES=$(comfy --json run --workflow my_workflow.json)
PROMPT_ID=$(echo "$RES" | jq -r .data.prompt_id)

# Watch until terminal, then collect outputs
comfy --json jobs watch "$PROMPT_ID" | comfy download

Prefer a single blocking call? Use --wait:

comfy run --workflow my_workflow.json --wait | comfy download

Track and manage jobs:

comfy jobs ls                 # local async submits + server queue/history
comfy jobs status <prompt_id> # one job
comfy jobs wait <id1> <id2>   # block until ALL reach a terminal state
comfy jobs cancel <prompt_id> # idempotent

Validate before you submit. Catch unknown nodes, missing models, and bad wiring before burning cloud compute:

comfy validate --workflow my_workflow.json

Start from a Template

The curated Comfy-Org/workflow_templates gallery is the fastest way to get a known-good workflow for a given task. You do not need to build from scratch.

comfy templates ls --type image --tag "Text to Image"   # browse
comfy templates show <name>                              # full metadata
comfy templates fetch <name> --out my.json               # pull the workflow JSON

The downloaded JSON is frontend-format. comfy run --where cloud auto-converts it to API format on submit.

Edit Workflows In Place

comfy workflow exposes the agent-tweakable slots in any frontend-format workflow and lets you override them. No manual JSON surgery.

comfy workflow slots my.json                 # list addressable slots
comfy workflow set-slot my.json 6.text="a fox in the snow"
comfy workflow vary my.json \
    --slot positive.text='["a cat","a dog","a fox"]' \
    --out-dir ./variants                     # fan out N variants

Saved workflows on Comfy Cloud:

comfy workflow list                          # your saved workflows
comfy workflow get <id> --out my.json
comfy workflow save my.json --name "My Flow"
comfy workflow delete <id>

For complex multi-step pipelines, compose small reusable fragments into one graph:

comfy workflow compose blueprints/my_pipeline.yaml -o workflows/my_pipeline.json
comfy workflow decompose my.json             # inverse: project a workflow into a fragment

Discover Nodes and Models

Introspect everything available on the resolved backend. Nodes:

comfy nodes search "checkpoint"              # fuzzy search
comfy nodes show KSampler                    # full schema: inputs, outputs, defaults
comfy nodes ls --produces IMAGE --limit 10   # filter by output type
comfy nodes ls --api-only                    # partner-API nodes only

Models:

comfy models list-folders                    # every model folder
comfy models search --text "wan2.2" --type lora
comfy models show wan2.2_vae.safetensors     # full metadata

Upload and Download Files

comfy upload photo.png video.mp4             # → server input directory
comfy download <prompt_id>                   # → ./outputs/

The idiomatic pipe:

comfy run --workflow flux.json --wait | comfy download

comfy download reads the prompt_id and output URLs from piped stdin automatically. No manual key extraction, no jq.

Manage Custom Nodes

comfy node install <NODE_NAME>

The tool uses cm-cli for custom node installation. See the ComfyUI Manager cm-cli docs for details.

Manage Models (Local)

Download models easily:

comfy model download --url <url> --relative-path models/checkpoints

JSON Output for Scripts and Agents

Every command accepts --json and emits the same envelope shape, making the CLI fully scriptable and agent-friendly:

{
  "ok": true,
  "command": "...",
  "version": "1.11.1",
  "where": "local | cloud | null",
  "data": { },
  "error": null
}

When error is present, read the hint and act on it:

comfy --json run --workflow my.json | jq '.error.hint'

The agent-facing surface is fully self-describing. Dump the entire command tree, output schemas, and error codes:

comfy --json discover

Agent Skills

Install the bundled Comfy agent skills into Claude Code, Cursor, and any AGENTS.md-aware tool, so your coding agent can drive the CLI directly:

comfy skills install
comfy skills list      # comfy, comfy-fragments, comfy-debug, comfy-relay, comfy-director
comfy skills status    # what's installed where

These are bundled CLI skills installed by comfy skills install. They are separate from the Comfy Skills repository, which hosts the comfy-cloud Claude Code plugin for Comfy Cloud MCP.

Contributing

Contributions are welcome. Open issues or submit pull requests on the comfy-cli GitHub repository. Refer to the Dev Guide for further details.

Analytics

Usage tracking helps improve the CLI. Disable it with:

comfy tracking disable

Re-enable tracking:

comfy tracking enable

You can also hard opt-out via the DO_NOT_TRACK or COMFY_NO_TELEMETRY environment variables.

​Overview

​Install CLI

​Quick Setup (Recommended)

​Install ComfyUI (Local)

​Run ComfyUI (Local)

​Comfy Cloud

​Generate with Partner Nodes

​Prerequisites

​First generation

​Common models

​Discover models

​Image editing with references

​Video generation (async jobs)

​JSON output for scripts

​Run Workflows (comfy run)

​Start from a Template

​Edit Workflows In Place

​Discover Nodes and Models

​Upload and Download Files

​Manage Custom Nodes

​Manage Models (Local)

​JSON Output for Scripts and Agents

​Agent Skills

​Contributing

​Analytics

Overview

Install CLI

Quick Setup (Recommended)

Install ComfyUI (Local)

Run ComfyUI (Local)

Comfy Cloud

Generate with Partner Nodes

Prerequisites

First generation

Common models

Discover models

Image editing with references

Video generation (async jobs)

JSON output for scripts

Run Workflows (`comfy run`)

Start from a Template

Edit Workflows In Place

Discover Nodes and Models

Upload and Download Files

Manage Custom Nodes

Manage Models (Local)

JSON Output for Scripts and Agents

Agent Skills

Contributing

Analytics