comfyui-mcp — drive ComfyUI with ANY LLM

The local-first, agent-native control plane for ComfyUI — an MCP server + live sidebar agent that generates images, video and audio, authors and runs workflows, manages models and custom nodes, and edits your live ComfyUI graph in natural language. Bring whatever model you have: Claude or ChatGPT on your subscription, Gemini on your Google login, a free local model via Ollama (fully offline), or any hosted model over one API key (DeepSeek, GLM, MiMo, Kimi, GPT, Claude via OpenRouter). Same tools, same panel, every tier — and the built-in LLM Arena scores them all on real ComfyUI tasks so you know exactly what your model can do. One config targets local installs, LAN, VPS, or Comfy Cloud.

One-click GPU pod — a ready-to-run ComfyUI with this project + Agent Panel + ComfyUI-Manager v2 preinstalled, on your own GPU. No setup.

Works on macOS, Linux, and Windows. Auto-detects your ComfyUI installation and port.

Stuck or have a question? Join the Discord — help, model tips, and release announcements.

108 MCP tools | 32 AI skills (Flux · WAN · LTX 2.3 video · Qwen · Z-Image · Ideogram 4 · ERNIE · ANIMA · model registry · Civitai · node authoring · launch/perf flags) | 13 installer packs | 11 slash commands | 4 autonomous agents | 4 hooks

The plugin ships expert skills that grow with every release — model-specific generation guides with curated download URLs, workflow recipes, troubleshooting, and custom-node authoring — so Claude knows the right sampler, CFG, resolution, and model files for each architecture without trial and error.

✅ Now available: the ComfyUI Agent Panel on ComfyUI-Manager & the Comfy Registry

An autonomous AI agent in your ComfyUI sidebar — on Claude, ChatGPT, Gemini, or ANY local/hosted LLM (Ollama and every OpenAI-compatible endpoint). Subscriptions work with no API key; local models work with no account at all. Pick a provider and it drives your live graph: edits, spatial layout, one-shot workflow/pack loads, rewind/rollback, a pending-message tray, activity cards, multi-tab — and it asks before spending paid API credits. Search comfyui-agent-panel in ComfyUI-Manager to install. Read more →

📖 Full documentation: comfyui-mcp.artokun.io/docs

Quick Start

1. Install ComfyUI (if you haven't already): ComfyUI Desktop or from source

2. Add the MCP server to your Claude Code config (~/.claude/settings.json):

{
  "mcpServers": {
    "comfyui": {
      "command": "npx",
      "args": ["-y", "comfyui-mcp"],
      "env": {
        "CIVITAI_API_TOKEN": ""
      }
    }
  }
}

3. Start using it. With ComfyUI running, ask Claude to generate an image:

> Generate an image of a sunset over mountains

Claude will find (or download) a checkpoint, build a workflow, execute it, and return the image.

Note: This runs as a standalone MCP server — no need to clone this repo. npx will download and run it automatically.

Scope: local, remote, or Comfy Cloud

comfyui-mcp is local-first: a self-hosted ComfyUI on Mac/Linux/Windows is the primary target, with the same agent reaching remote installs (RunPod, VPS, LAN, reverse-proxied) from one config. Local-first, not local-only.

More than a bridge. Most ComfyUI MCP servers are thin connectors — they forward a prompt and hand back an image. comfyui-mcp is a full control plane: it authors and edits the graph node-by-node, runs and iterates on workflows, manages models and custom nodes, and ships model-specific expertise (samplers, CFG, resolutions, curated model URLs) so the agent gets it right without trial and error. If you want a minimal local relay, a lightweight server is fine; if you want an agent that actually operates ComfyUI, that's this project.

For Comfy Cloud users, Comfy-Org ships an official Comfy Cloud MCP (currently invite-only beta) which is cloud-exclusive and maintained by the Comfy team. comfyui-mcp also includes a community cloud-mode (set COMFYUI_API_KEY — see Deployment modes) so a single MCP can target all three deployment shapes from one config; pick whichever fits your workflow.

Remote / hosted connector (one command)

Want to use comfyui-mcp from Claude Desktop's Custom Connectors or any remote client — like Comfy's own cloud.comfy.org/mcp connector? Run it as an authenticated, publicly-reachable Streamable-HTTP server with one flag:

npx -y comfyui-mcp@latest --tunnel

This forces the HTTP transport, generates an auth token, opens a cloudflared quick tunnel, and prints a ready-to-paste https://…/mcp URL + token + Claude Desktop connector snippet. Auth accepts Authorization: Bearer <token> or X-API-Key: <token> (matching Comfy Cloud's convention). See the Remote / hosted connector guide for the full walkthrough and headless usage.

Auth is opt-in: with no COMFYUI_MCP_HTTP_TOKEN set and no --tunnel, the default stdio (and plain --http on loopback) behavior is unchanged — open and local. OAuth (Comfy's browser sign-in flow) is a planned follow-up.

Claude Code Plugin

This package also ships as a Claude Code plugin, providing slash commands, skills, agents, and hooks on top of the MCP tools.

Install as a plugin

# In Claude Code
/plugin marketplace add artokun/comfyui-mcp
/plugin install comfy

Slash commands

Command	Description
`/comfy:gen <prompt>`	Generate an image from a text description — auto-selects checkpoint, builds workflow, returns image
`/comfy:viz <workflow>`	Visualize a workflow as a Mermaid diagram with nodes grouped by category
`/comfy:node-skill <pack>`	Generate a Claude skill for a custom node pack from Registry ID or GitHub URL
`/comfy:debug [prompt_id]`	Diagnose why a workflow failed — reads history, logs, traces root cause, suggests fixes
`/comfy:batch <prompt, params>`	Parameter sweep generation across cfg, sampler, steps, seed, etc.
`/comfy:convert <file>`	Convert between UI format and API format workflows
`/comfy:install <pack>`	Install a custom node pack — git clone, pip install, optional restart
`/comfy:gallery [filter]`	Browse generated outputs with metadata — filter by date, count, or filename
`/comfy:compare <a vs b>`	Diff two workflows side by side — shows added/removed nodes and changed parameters
`/comfy:recipe <name> <prompt>`	Multi-step recipes: `portrait`, `hires-fix`, `style-transfer`, `product-shot`

Built-in skills

32 skills total — model-family guides (Flux, WAN, LTX 2.3, Qwen, Z-Image, Ideogram 4, ERNIE, ANIMA + anime / WAN / Z-Image LoRA training), the model-registry (curated download URLs), the civitai pairing skill, node authoring, the launch/performance-flags matrix, and the core four below. Full list on the plugin docs page.

Installer packs. packs/ bundles 13 one-command ComfyUI setups — ANIMA, Ideogram 4, LTX-2.3, ERNIE, WAN (animate / longer-videos / transparent), Qwen (image / image-edit), Z-Image (turbo / base / xy-plot) and artokun-flow (WAN Animate — replace / animate). Each is a manifest of custom nodes + model URLs + workflow that drives both apply_manifest and generated install-windows.bat / install-runpod.sh, with CI that validates every model link + payload size. See packs/README.md.

Skill	Description
comfyui-core	Workflow format, node types, data flow patterns, pipeline architecture, MCP tool usage guide
prompt-engineering	CLIP weight syntax `(word:1.3)`, BREAK tokens, embeddings, model-specific prompting for SD1.5/SDXL/Flux/SD3
troubleshooting	Common error catalog — OOM, dtype mismatches, missing nodes, NaN tensors, black images, CUDA errors, with VRAM estimates per model
model-compatibility	Compatibility matrix — loaders, resolutions, CFG, samplers, ControlNets, LoRAs, and VAEs per model family (SD1.5/SDXL/Turbo/Lightning/Flux/SD3/LTXV)

Agents

Agent	Model	Description
comfy-explorer	Sonnet	Researches custom node packs — reads docs, queries `/object_info`, generates comprehensive skill files
comfy-debugger	Sonnet	Autonomously diagnoses workflow failures — gathers logs + history, identifies failing node, checks models + custom nodes, proposes and optionally applies fixes
comfy-optimizer	Sonnet	Analyzes workflows for performance — detects redundant nodes, VRAM waste, wrong CFG/steps for model family, precision issues, suggests optimizations

Hooks

Event	Trigger	Action
PreToolUse	`enqueue_workflow`	VRAM watchdog — checks GPU memory via `/system_stats` and warns if < 1GB free before execution
PreToolUse	`stop_comfyui`, `restart_comfyui`	Save warning — prompts user to save unsaved workflow changes before stopping ComfyUI
PostToolUse	Any comfyui tool	Job completion notify — checks for completed jobs and injects completion summaries into the conversation

Background Scripts

Script	Description
`monitor-progress.mjs`	Progress monitor — connects to ComfyUI's WebSocket for real-time step progress (e.g., `step 5/14 (36%)`). Run as a background Bash task after enqueuing workflows. Reports completion with output filenames, errors with node details. Replaces polling `get_job_status` in a loop.

Panel agent (Claude · ChatGPT · Gemini · any local/hosted LLM)

Beyond the headless MCP server, this package ships the panel orchestrator that powers the ComfyUI Agent Panel — an autonomous agent embedded in ComfyUI's sidebar that drives the live canvas. It runs in the background on your own subscription (Claude or ChatGPT), started on demand by the panel's Connect button:

npx -y comfyui-mcp@latest connect

Drive a REMOTE ComfyUI from your own machine (`connect`)

When ComfyUI runs somewhere with no Node/agent (a RunPod pod, a cloud box) you can still run the agent on your machine and drive that remote ComfyUI — no agent login on the box, nothing to install or configure remotely:

npx -y comfyui-mcp@latest connect https://abcd1234-8188.proxy.runpod.net

This is sugar for --panel-orchestrator with COMFYUI_URL set from the URL: the orchestrator runs locally on your Claude/ChatGPT login and reaches the remote ComfyUI over its public proxy URL. For a remote HTTPS pod, connect automatically opens a secure, token-gated wss:// tunnel (via Cloudflare) to the local agent bridge and hands the pod's panel that URL — so the pod's HTTPS page reaches your machine with no browser prompt, in any browser (a secure page can't open a plain ws:// socket to your box — mixed content / Private Network Access). A local ComfyUI uses the plain ws://127.0.0.1:9180 loopback bridge; add --insecure-bridge to force that loopback for a remote pod (then arrange your own path to it, e.g. an SSH port-forward). Either way the panel JS runs in your local browser and the agent — and your login — run only on your machine, so nothing is installed remotely.

To finish: open the remote ComfyUI in your browser, turn on Settings → General → "Use external/local orchestrator (advanced)" in the Agent panel, then click Connect. (In that mode the panel connects straight to the local bridge instead of asking the ComfyUI host to spawn an orchestrator it can't run.)

Multi-provider, full parity. The orchestrator depends on a provider-neutral AgentBackend port (dependency injection), with two adapters:

ClaudeBackend — the Claude Agent SDK (@anthropic-ai/claude-agent-sdk), a persistent streaming session over the claude.ai subscription (OAuth, no key).
CodexBackend — OpenAI Codex over the codex app-server JSON-RPC protocol (@openai/codex), on the ChatGPT subscription (codex login, no key).

Both are optional dependencies, and the panel picks a provider, not a port — each backend runs its own orchestrator on its own loopback bridge port. A capability matrix lets the panel degrade gracefully (e.g. conversation-rollback is Claude-only today, since the Codex app-server resumes whole threads only).

The live-canvas tools and model knowledge are identical across providers. The panel_* tool definitions live in one shared list, registered onto both the in-process Claude SDK MCP server and a @modelcontextprotocol/sdk server over a loopback streamable-HTTP MCP that the orchestrator hosts for Codex (which can only host config-declared MCP servers). The headless comfyui MCP is likewise injected into both — in-process for Claude, declared via codex app-server -c mcp_servers for ChatGPT — so generation, models, and workflow tools are the same everywhere.

New tools that give every backend the same expertise and a cost guardrail:

Tool	Description
`list_skills` / `read_skill`	Discover and read bundled model-family + workflow skills — the knowledge Claude loads natively, exposed to any MCP client (e.g. the Codex backend)
`list_packs` / `read_pack_workflow`	List one-command installer packs (custom nodes + weights + ready workflow; all local-GPU / free) and read a pack's graph
`list_workflow_templates`	List the connected ComfyUI's official workflow templates (the templates package + custom-node-provided templates)
`check_workflow_runtime`	Classify a workflow as local (your GPU, free) or api / mixed / unknown (hosted API nodes = paid credits) so the agent asks before spending paid API credits
`panel_load_workflow`	(panel tool) Load a full workflow onto the live canvas in one shot — by bundled `pack` name (read server-side, never shuttled through chat) or by graph JSON
`panel_strip_workflow` / `panel_slice_workflow`	(panel tools) De-virtualize a tangled graph (Get/Set buses, Reroutes, subgraphs, bypass → real connections) or carve one rgthree-toggled pipeline out of a monolith — by `pack`, server-side `path`, or inline graph; for understanding/rebuilding expert workflows without hand-tracing

See the design doc — docs/design/agent-backend-injection.md — for the port, the capability matrix, and the per-provider "clink" points, and the panel docs for the full sidebar UX.

MCP Tools

108 tools across workflow execution, generation, iteration, composition, models, and more:

Image Generation (high-level)

Tool	Description
`generate_image`	Generate from a text prompt — builds a txt2img workflow, fills unspecified params from your defaults, auto-selects a checkpoint
`generate_with_controlnet`	Generate conditioned by a ControlNet image (pose/depth/canny/normal) + prompt
`generate_with_ip_adapter`	Generate guided by a reference image's style/subject via IP-Adapter (needs ComfyUI_IPAdapter_plus)

Audio Generation (high-level)

Tool	Description
`generate_audio`	Generate audio from a text prompt — supports ACE Step 1.5 (music with lyrics/structure) and Stable Audio 3 (music, instruments, SFX); auto-selects local models

Assets & Iteration

Tool	Description
`view_image`	Return a generated asset's bytes as an inline image so the agent can see the result
`analyze_color`	Palette / contrast / color statistics for a generated image (dominant colors, average + luminance stats, contrast checks) so the agent can reason about color without a vision round-trip
`regenerate`	Re-run the workflow that produced an `asset_id`, with optional parameter overrides
`list_assets`	Browse recently generated assets (newest-first) by `asset_id`
`get_asset_metadata`	Full provenance for an asset, including the originating workflow

Defaults

Tool	Description
`get_defaults`	Show merged generation defaults with per-source attribution
`set_defaults`	Update runtime defaults; `persist: true` writes the config file

Workflow Execution

Tool	Description
`enqueue_workflow`	Submit a workflow (API format JSON) — returns `prompt_id` immediately, non-blocking
`get_job_status`	Check execution status of a job by prompt ID
`get_queue`	View the current execution queue (running + pending)
`get_queued_workflow`	Inspect the full workflow payload for one pending queue item
`move_queued_job`	Move a pending job to the front/back by requeueing it with a new prompt ID
`edit_queued_job`	Patch or replace a pending queued workflow and requeue it with a new prompt ID
`cancel_job`	Interrupt the currently running job — escalates (interrupt → verify → `/free`) and reports WEDGED if it won't die; `clear_pending: true` also drops all pending jobs in the same call
`get_system_stats`	Get system info — GPU, VRAM, Python version, OS

Workflow Visualization

Tool	Description
`visualize_workflow`	Convert a workflow to a Mermaid flowchart with nodes grouped by category
`mermaid_to_workflow`	Convert a Mermaid diagram back to executable workflow JSON

Workflow Composition

Tool	Description
`create_workflow`	Generate a workflow from templates: `txt2img`, `img2img`, `upscale`, `inpaint`, `controlnet`, `ip_adapter`, `ace_step_15`, `stable_audio_3`
`modify_workflow`	Apply operations: `set_input`, `add_node`, `remove_node`, `connect`, `insert_between`
`get_node_info`	Query available node types from ComfyUI's `/object_info` endpoint

Workflow Validation

Tool	Description
`validate_workflow`	Dry-run validation — checks missing nodes, broken connections, invalid output indices, missing model files

Workflow Library

Tool	Description
`list_workflows`	List saved workflows from ComfyUI's user library
`get_workflow`	Load a specific saved workflow by filename
`strip_workflow`	De-virtualize any workflow (absolute path, library filename, or inline graph) — resolve GetNode/SetNode buses, Reroutes, subgraph defs, and bypassed nodes into real connections and return the flat graph. Reads ANY path server-side, so it loads ad-hoc/expert workflows the cached library can't.
`slice_workflow`	Un-chunk a toggle-template monolith — slice ONE rgthree Fast-Groups-Bypass-toggled pipeline out into a standalone activated graph (seed from the named groups' output nodes, backward-closure, un-bypass). Pair with `strip_workflow` to then flatten the buses.
`save_workflow`	Save a workflow to the ComfyUI user library

Image Management

Tool	Description
`upload_image`	Copy a local image into ComfyUI's `input/` directory for img2img, inpaint, or ControlNet
`workflow_from_image`	Extract embedded workflow metadata from a ComfyUI-generated PNG (reads `prompt` and `workflow` tEXt chunks)
`list_output_images`	Browse recently generated images and videos from the output directory, sorted newest-first — recurses into subfolders (e.g. SaveVideo's `output/video/…`) and returns each result's `subfolder`

Model Management

Tool	Description
`search_models`	Search HuggingFace for compatible models (checkpoints, LoRAs, VAEs, etc.)
`download_model`	Download a model from a URL to the correct ComfyUI subdirectory
`list_local_models`	List installed models by type: checkpoints, loras, vae, upscale_models, controlnet, embeddings, clip, unet, diffusion_models, text_encoders
`list_extra_paths`	View standalone or Desktop ComfyUI extra search-path config
`add_extra_path`	Add a model/custom_nodes search path to the extra paths YAML
`remove_extra_path`	Remove a stored extra search path from the extra paths YAML

Memory Management

Tool	Description
`clear_vram`	Free GPU VRAM by unloading cached models — calls ComfyUI's `/free` endpoint, reports before/after stats
`get_embeddings`	List installed textual inversion embeddings

Registry & Discovery

Tool	Description
`search_custom_nodes`	Search the ComfyUI Registry for custom node packs by keyword
`get_node_pack_details`	Get full details of a custom node pack (description, author, nodes, install info)
`generate_node_skill`	Generate a Claude skill `.md` file from a Registry ID or GitHub URL
`comfy_cli_search_nodes`	Search actual loaded node classes through official `comfy nodes search`

Official comfy-cli

Install comfy-cli 1.11.1 or newer to enable the official JSON-backed tools. The MCP resolves comfy from COMFY_CLI_PATH, PATH, or the selected workspace's .venv/venv. Local custom-node operations prefer comfy node when a supported CLI is available and otherwise fall back to Manager HTTP; remote targets retain Manager HTTP.

Tool	Description
`comfy_cli_status`	Inspect version, selected workspace (`which`), environment, or the self-describing command surface
`comfy_cli_server`	Start, stop, or restart a CLI-managed background ComfyUI
`comfy_cli_jobs`	List, inspect, wait for, watch, or cancel local/cloud jobs
`comfy_cli_workflow`	Validate or run workflow files through the official CLI
`comfy_cli_transfer`	Upload inputs or download completed job outputs
`comfy_cli_models`	Browse/search local or cloud models; download/remove workspace model files
`comfy_cli_skills`	List/show/validate/install/status/uninstall official bundled agent skills

Diagnostics

Tool	Description
`get_logs`	Get ComfyUI server logs with optional keyword filter (e.g., `error`, `warning`, a node name)
`get_history`	Get execution history with full error details, Python tracebacks, timing, and cached node info

Process Control

Tool	Description
`stop_comfyui`	Stop the running ComfyUI process (saves PID and launch args for restart)
`start_comfyui`	Start ComfyUI using info saved from a previous stop
`restart_comfyui`	Stop and restart ComfyUI, preserving all launch arguments

Generation Tracker

Tool	Description
`suggest_settings`	Suggest proven sampler/scheduler/steps/CFG settings from local generation history — query by model family, LoRA hash, or text search
`generation_stats`	Show local generation tracking statistics — total runs, unique combos, breakdown by model family

Every enqueue_workflow call automatically logs settings to a local SQLite database (generations.db). Same settings combos get a reuse_count bump instead of duplicates, creating a natural popularity signal. Models and LoRAs are identified by content hash (AutoV2 / SHA256), not filenames — so renamed files still group together.

# View local stats from the CLI
npm run generations:stats

Model Settings

Community-maintained preset library (model-settings.json) with research-backed sampler, scheduler, steps, and CFG values for 10+ model families. User overrides in model-settings.user.jsonc (auto-created from template on install, gitignored).

Examples

Generate an image

> /comfy:gen a cyberpunk city at night with neon lights

Claude will:

Check installed checkpoints (download one if needed)
Build a txt2img workflow with your prompt
Execute it on ComfyUI
Return the generated image

Visualize a workflow

> /comfy:viz ~/workflows/my-workflow.json

Produces a Mermaid diagram with nodes grouped by category:

flowchart LR
  subgraph Loaders
    1["CheckpointLoaderSimple"]
  end
  subgraph Conditioning
    2(["Positive Prompt"])
    3(["Negative Prompt"])
  end
  subgraph Sampling
    5{{"KSampler<br/>steps:20 cfg:8"}}
  end
  1 -->|MODEL| 5
  2 -->|CONDITIONING| 5
  3 -->|CONDITIONING| 5

Debug a failed workflow

> /comfy:debug

Automatically reads the last execution history and logs, identifies the failing node, checks for missing models or node packs, and suggests a fix.

> /comfy:debug abc123-def456

Diagnose a specific execution by prompt ID.

Parameter sweep

> /comfy:batch a cat in a field, cfg:5-10:2, sampler:euler,dpmpp_2m

Generates a grid of images across all parameter combinations and presents a summary table with results.

Supported sweep parameters: cfg, steps, sampler, scheduler, seed, denoise, width, height.

Multi-step recipes

> /comfy:recipe hires-fix a dramatic fantasy landscape with castles

Runs a two-pass pipeline: txt2img at 512x768, then img2img upscale to 1024x1536 with detail enhancement.

Available recipes:

Recipe	Description
`portrait`	Generate at 1024x1024, then 2x upscale to 2048x2048
`hires-fix`	Low-res generation → img2img upscale with denoise 0.4-0.5
`style-transfer`	Apply a style prompt to an existing image via img2img
`product-shot`	Product image with clean white background

Convert workflow format

> /comfy:convert ~/workflows/my-ui-workflow.json

Converts between ComfyUI's UI format (nodes + links arrays) and API format (node IDs → {class_type, inputs}).

Install a custom node pack

> /comfy:install comfyui-impact-pack

Searches the registry, shows details, clones the repo to custom_nodes/, installs dependencies, and offers to restart ComfyUI.

Browse output gallery

> /comfy:gallery last 5
> /comfy:gallery today

Lists recent outputs with embedded metadata — shows checkpoint, prompt, seed, steps, CFG, sampler for each image.

Compare workflows

> /comfy:compare workflow-a.json vs workflow-b.json

Shows added/removed nodes, changed parameters (old → new values), and optional Mermaid diagrams for visual comparison.

Validate before running

> Validate this workflow before I run it

Checks for missing node types, broken connections, invalid output indices, and missing model files — without executing.

Manage models

> What checkpoints do I have installed?
> Search HuggingFace for SDXL turbo models
> Download this model to my checkpoints folder

Manage VRAM

> Free my VRAM
> What embeddings do I have?

Extract workflow from an image

> Extract the workflow from this image: ~/outputs/ComfyUI_00042_.png

Reads the PNG metadata chunks to recover the exact workflow and prompt used to generate the image.

Explore custom nodes

> /comfy:node-skill comfyui-impact-pack

Generates a comprehensive skill file documenting every node, its inputs/outputs, and usage patterns.

Process control

> Restart ComfyUI
> Stop ComfyUI
> Start ComfyUI back up

Configuration

The server auto-detects your ComfyUI installation and port. Override with environment variables if needed.

Where to put keys and overrides:

Panel users: the API Keys card (▾ menu next to "connected") — stored in ~/.comfyui-mcp/panel-secrets.json, applied immediately, no restart.
MCP-only setups (Claude Desktop, Claude Code, etc.): the env block of your MCP client config, as shown in the setup examples above.
Real environment variables always take precedence over stored keys. (For development, ~/.comfyui-mcp/.env is also loaded as an override file — regular installs shouldn't need it.)

Deployment modes

comfyui-mcp operates in one of three modes, auto-selected from the environment:

Mode	Trigger	Local FS / process tools?
Local	default	yes
Remote	`--comfyui-url` / `COMFYUI_URL` points at a non-loopback host, or `--force-remote` is set	no — server skips `COMFYUI_PATH` auto-detection so stale local installs can't silently absorb uploads
Cloud	`COMFYUI_API_KEY` is set (targets Comfy Cloud)	no — HTTP primitives route via `cloud.comfy.org` over `X-API-Key`; WebSocket and local-only tools throw `CLOUD_UNSUPPORTED`

Some setups (e.g. dstack driving ComfyUI on RunPod) port-forward a remote ComfyUI back to localhost:8188, so the loopback check above gets it wrong — the install isn't actually local. Pass --force-remote (or set COMFYUI_MCP_FORCE_REMOTE=1) alongside --comfyui-url/COMFYUI_URL to force remote mode regardless of hostname:

npx -y comfyui-mcp@latest --comfyui-url http://localhost:8188 --force-remote

Variable	Default	Description
`COMFYUI_URL`		Full ComfyUI URL, e.g. `https://comfy.example.com:8443` — overrides `COMFYUI_HOST`/`PORT`/`SSL` and skips auto-detection. A path prefix is preserved (e.g. `https://host/comfyapi`) for reverse-proxied instances. Non-loopback hosts opt into remote mode.
`COMFYUI_MCP_FORCE_REMOTE`		Set to `1`/`true` (or pass `--force-remote`) to force remote mode even when `COMFYUI_URL`/`--comfyui-url` resolves to a loopback host — for port-forwarded remote installs (e.g. dstack/RunPod) that are reachable at `localhost`. No effect without a `COMFYUI_URL`/`--comfyui-url`.
`COMFYUI_HOST`	`127.0.0.1`	ComfyUI server address
`COMFYUI_PORT`	(auto-detect)	ComfyUI server port (tries 8188, then 8000)
`COMFYUI_PATH`	(auto-detect)	Path to ComfyUI data directory. Auto-detection suppressed in remote/cloud modes.
`COMFY_CLI_PATH`	(auto-detect)	Path to the official `comfy` executable (comfy-cli >=1.11.1). Resolution also checks `PATH` and the selected workspace's `.venv`/`venv`.
`COMFYUI_PYTHON`	`python`	Python interpreter used by legacy git-clone dependency fallbacks. Point it at your ComfyUI venv's Python when needed.
`COMFYUI_MCP_BRIDGE_HOST`	`127.0.0.1`	Panel-bridge bind host. Set `0.0.0.0` (or a LAN IP) to run the orchestrator on a 24/7 server and connect panels from other machines — requires a token (below); the orchestrator prints a ready-to-paste `ws://…/?token=…` Bridge URL.
`COMFYUI_MCP_BRIDGE_TOKEN`	(generated when needed)	Shared secret gating every bridge connection (checked constant-time on the WS upgrade). Mandatory for a non-loopback `COMFYUI_MCP_BRIDGE_HOST`; pin it so the Bridge URL survives restarts. Never logged beyond the startup banner.
`COMFYUI_MCP_DATA_DIR`	`~/.comfyui-mcp`	Base dir for per-instance data (the `generations.db` used by `suggest_settings`) when there's no local `COMFYUI_PATH` (remote/cloud/undetected). Scoped per target under `instances/<host_port>/`.
`COMFYUI_API_KEY`		Comfy Cloud API key. When set, cloud mode is active and the server talks to `cloud.comfy.org`. Never logged.
`COMFYUI_CLOUD_URL`	`https://cloud.comfy.org`	Override the Comfy Cloud endpoint (testing/staging).
`COMFYUI_AUTH_TOKEN`		Generic auth token for a self-hosted ComfyUI behind a reverse proxy / API gateway (distinct from Comfy Cloud). When set, attached to every ComfyUI request. Never logged.
`COMFYUI_AUTH_HEADER`	`Authorization`	Header name for `COMFYUI_AUTH_TOKEN` (e.g. `X-API-Key`).
`COMFYUI_AUTH_SCHEME`	`Bearer` for `Authorization`, else none	Scheme prefix on the token value (e.g. `Bearer`, `Token`).
`CIVITAI_API_TOKEN`		CivitAI API token for model downloads
`HUGGINGFACE_TOKEN`		HuggingFace token for higher API rate limits
`GITHUB_TOKEN`		GitHub token for skill generation (avoids rate limits)
`REGISTRY_ACCESS_TOKEN`		Comfy Registry API key for `publish_custom_node` (env-only, never logged)
`COMFYUI_DOWNLOAD_CACHE_DIR`	`~/.comfyui-mcp/cache`	Content-addressed model-download cache (dedup + concurrent coalescing)
`COMFYUI_LRU_CACHE_SIZE_GB`	`0`	Cap the download cache in GB; `0` disables LRU eviction
`COMFYUI_STARTUP_CHECK_INTERVAL_S` / `…_MAX_TRIES`	`1` / `20`	Readiness-probe interval + max tries when starting a local ComfyUI
`COMFYUI_ALWAYS_RESTART`	`false`	Auto-restart a crashed local ComfyUI (bounded by `COMFYUI_RESTART_MAX_ATTEMPTS` / `COMFYUI_RESTART_WINDOW_S`)
`COMFYUI_MCP_STALL_S`	`180`	Render-wedge watchdog: seconds a sampler step can re-emit the same progress before a STALL/BACKLOG note is prepended to the agent's next turn (clamped 15–3600s; live-tunable from the panel)
`COMFYUI_MCP_INTERRUPT_S`	`30`	Seconds `cancel_job` waits for an interrupt to actually stop a job before escalating to `/free` and reporting it wedged
`LOG_LEVEL`	`info`	Logging verbosity: `debug`, `info`, `warn`, `error`

Transports

The server speaks stdio by default (what Claude Code, Claude Desktop, and the MCP Inspector expect — no flags needed). For MCP gateways, remote/hosted setups, or fetch-based clients, opt into streamable-HTTP:

# stdio (default)
npx -y comfyui-mcp@latest

# streamable-HTTP on http://127.0.0.1:9100/mcp
npx -y comfyui-mcp@latest --http
npx -y comfyui-mcp@latest --http --host 0.0.0.0 --port 9100   # bind/port overrides

Flag	Env	Default	Description
`--http` / `--transport http`	`MCP_TRANSPORT=http`	`stdio`	Serve streamable-HTTP at `/mcp` instead of stdio
`--host <h>`	`MCP_HOST`	`127.0.0.1`	HTTP bind host (use `0.0.0.0` to expose)
`--port <n>`	`MCP_PORT`	`9100`	HTTP port
`--comfyui-url <url>`	`COMFYUI_URL`	(auto-detect)	Target a specific (incl. remote) ComfyUI
`--force-remote`	`COMFYUI_MCP_FORCE_REMOTE`	`false`	Force remote mode for a loopback `--comfyui-url` (e.g. dstack/RunPod port-forwards to `localhost`)

Other agents & local LLMs (Hermes, OpenClaw, Copilot CLI, Ollama)

comfyui-mcp has first-class support for non-Claude harnesses. One command writes the server entry into the harness's own config (merging, not clobbering):

npx -y comfyui-mcp setup hermes     # → ~/.hermes/config.yaml      (compact by default)
npx -y comfyui-mcp setup openclaw   # → ~/.openclaw/openclaw.json  (compact by default)
npx -y comfyui-mcp setup copilot    # → ~/.copilot/mcp-config.json (full by default)
# flags: --compact | --full, --comfyui-url <url>, --dry-run

Model requirements: tool calling is a hard requirement (no tool calling = doesn't work). Thinking and vision are strongly recommended — without thinking, multi-step tool chains degrade; without vision the agent can generate but can't see its own outputs.

For small/local models, compact tool mode (--compact / COMFYUI_MCP_TOOL_MODE=compact) registers 3 meta-tools (list_tools → describe_tool → call_tool) instead of the full ~200-schema surface, pulling schemas into context one tool at a time. Run it locally for free with our fine-tuned models: ollama pull artokun/gemma4-comfyui-mcp:e4b (also :e2b for ~2 GB VRAM, :12b for ~8 GB) — Gemma 4 QLoRA-trained on 1,055 server-verified trajectories over the full comfyui-mcp tool surface, and the panel's Ollama default. Stock gemma4:*/qwen3:4b also validated end-to-end (npm run test:local-llm); gemma3 has no native tool calling and is unsupported. Full guide — hosted-model guidance (DeepSeek/MiMo/GLM class), per-harness setup, troubleshooting: Local LLMs & other agents.

Flag	Env	Default	Description
`setup <agent>`			Write the comfyui entry into hermes / openclaw / copilot config, then exit
`--compact` / `--tool-mode compact`	`COMFYUI_MCP_TOOL_MODE=compact`	`full`	Register 3 meta-tools instead of the full ~200-schema surface

Other agents & local LLMs (Hermes, OpenClaw, Copilot CLI, Ollama)

comfyui-mcp has first-class support for non-Claude harnesses. One command writes the server entry into the harness's own config (merging, not clobbering):

npx -y comfyui-mcp setup hermes     # → ~/.hermes/config.yaml      (compact by default)
npx -y comfyui-mcp setup openclaw   # → ~/.openclaw/openclaw.json  (compact by default)
npx -y comfyui-mcp setup copilot    # → ~/.copilot/mcp-config.json (full by default)
# flags: --compact | --full, --comfyui-url <url>, --dry-run

Flag	Env	Default	Description
`setup <agent>`			Write the comfyui entry into hermes / openclaw / copilot config, then exit
`--compact` / `--tool-mode compact`	`COMFYUI_MC

Comfyui MCP

README

comfyui-mcp — drive ComfyUI with ANY LLM

✅ Now available: the ComfyUI Agent Panel on ComfyUI-Manager & the Comfy Registry

Quick Start

Scope: local, remote, or Comfy Cloud

Remote / hosted connector (one command)

Claude Code Plugin

Install as a plugin

Slash commands

Built-in skills

Agents

Hooks

Background Scripts

Panel agent (Claude · ChatGPT · Gemini · any local/hosted LLM)

Drive a REMOTE ComfyUI from your own machine (connect)

MCP Tools

Image Generation (high-level)

Audio Generation (high-level)

Assets & Iteration

Defaults

Workflow Execution

Workflow Visualization

Workflow Composition

Workflow Validation

Workflow Library

Image Management

Model Management

Memory Management

Registry & Discovery

Official comfy-cli

Diagnostics

Process Control

Generation Tracker

Model Settings

Examples

Generate an image

Visualize a workflow

Debug a failed workflow

Parameter sweep

Multi-step recipes

Convert workflow format

Install a custom node pack

Browse output gallery

Compare workflows

Validate before running

Manage models

Manage VRAM

Extract workflow from an image

Explore custom nodes

Process control

Configuration

Deployment modes

Transports

Other agents & local LLMs (Hermes, OpenClaw, Copilot CLI, Ollama)

Other agents & local LLMs (Hermes, OpenClaw, Copilot CLI, Ollama)

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Drive a REMOTE ComfyUI from your own machine (`connect`)