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.
Works on macOS, Linux, and Windows. Auto-detects your ComfyUI installation and port.
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-panelin 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.
npxwill 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_TOKENset and no--tunnel, the default stdio (and plain--httpon 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 bothapply_manifestand generatedinstall-windows.bat/install-runpod.sh, with CI that validates every model link + payload size. Seepacks/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 thecodex app-serverJSON-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 |
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:
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. |
COMFYUI_PYTHON | python | Python interpreter for cm-cli subprocess operations (useCmCli, sync_node_dependencies) — point it at your ComfyUI venv's python. cm-cli needs the local filesystem, so these are local-mode only; on remote targets use the Manager HTTP path (the default). |
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. Validated
end-to-end via Ollama with gemma4:e4b, gemma4:e2b, and qwen3:4b
(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 |
Remote ComfyUI
Point the server at a ComfyUI running anywhere — no local install required:
npx -y comfyui-mcp@latest --comfyui-url http://192.168.1.50:8188
npx -y comfyui-mcp@latest --http --comfyui-url https://comfy.example.com:8443
Behind a reverse proxy / API gateway (path prefix + auth header) — for a
self-hosted ComfyUI exposed under a prefixed route with its own auth layer (this
is not Comfy Cloud, which is COMFYUI_API_KEY):
COMFYUI_URL=https://gateway.example.com/comfyapi \
COMFYUI_AUTH_TOKEN=your-token \
npx -y comfyui-mcp@latest --http # → Authorization: Bearer your-token, requests under /comfyapi
# custom header / scheme:
COMFYUI_URL=https://gateway.example.com/comfyapi \
COMFYUI_AUTH_HEADER=X-API-Key COMFYUI_AUTH_TOKEN=your-token \
npx -y comfyui-mcp@latest --http # → X-API-Key: your-token
Auto-detection
Port: Probes 8188 (CLI default) then 8000 (Desktop app default) via /system_stats.
Path: Checks common locations in order:
~/Documents/ComfyUI(macOS/Windows Desktop app data directory)~/Library/Application Support/ComfyUI(macOS)~/AppData/Local/Programs/ComfyUI/resources/ComfyUI(Windows Desktop app install)~/AppData/Local/ComfyUI(Windows)~/ComfyUI,~/code/ComfyUI,~/projects/ComfyUI,~/src/ComfyUI/opt/ComfyUI,~/.local/share/ComfyUI(Linux)- Scans
~/Documentsand~/My Documentsfor any directory containing "ComfyUI"
Set COMFYUI_PATH to skip detection and use an explicit path.
How It Works
The server communicates with ComfyUI through its REST API and WebSocket interface:
- WebSocket — enqueue workflows, receive real-time progress updates (step-by-step via background monitor script), get execution results
- REST API — system stats, node definitions (
/object_info), logs, history, queue management, workflow library, VRAM control (/free), embeddings - File system — read/write models directory, detect installation paths, upload images, extract PNG metadata, browse outputs
- External APIs — HuggingFace (model search), ComfyUI Registry (custom node discovery), GitHub (skill generation), CivitAI (model downloads)
All communication with the MCP client (Claude Code) happens over stdio using the Model Context Protocol. Logs go to stderr to avoid polluting the protocol stream.
Development
Prerequisites
Setup
git clone https://github.com/artokun/comfyui-mcp.git
cd comfyui-mcp
npm install
Scripts
| Script | Description |
|---|---|
npm run dev | Run from source with tsx (hot reload) |
npm run build | Compile TypeScript to dist/ |
npm start | Run compiled output |
npm test | Run unit tests (vitest) |
npm run test:integration | Run integration tests (requires running ComfyUI) |
npm run lint | Type-check without emitting |
npm run generations:stats | Show local generation tracking statistics |
npm run sync-agents | Sync Claude skills/commands/hooks to Google Antigravity, OpenCode, and other AI IDE formats that supports .agents files |
Local testing with Claude Code
Point Claude Code at your local build instead of the npm package:
{
"mcpServers": {
"comfyui": {
"command": "node",
"args": ["/path/to/comfyui-mcp/dist/index.js"],
"env": {}
}
}
}
Or test the plugin directly:
claude --plugin-dir ./plugin
Project structure
model-settings.json # Community-maintained model presets (shipped)
model-settings.user.jsonc.example # User override template (copied on install)
scripts/
postinstall.mjs # Auto-creates user config from template
generation-stats.mjs # CLI: npm run generations:stats
src/
index.ts # MCP server entry point (stdio transport)
config.ts # Auto-detection & environment config
comfyui/
client.ts # ComfyUI WebSocket/HTTP client wrapper
types.ts # TypeScript interfaces
services/
workflow-executor.ts # Execute workflows, handle images & errors
workflow-composer.ts # Templates (txt2img, img2img, upscale, inpaint)
workflow-validator.ts # Dry-run validation (missing nodes, models, connections)
image-management.ts # Upload images, extract PNG metadata, list outputs
mermaid-converter.ts # Workflow → Mermaid diagram
workflow-converter.ts # UI → API: de-virtualize Get/Set buses + Reroutes, expand subgraphs, resolve bypass (powers strip_workflow)
workflow-slicer.ts # sliceWorkflow() — rgthree Fast-Groups-Bypass pipeline un-chunker (shared by the CLI + slice_workflow)
mermaid-parser.ts # Mermaid diagram → Workflow
model-resolver.ts # HuggingFace search, local models, downloads
generation-tracker.ts # SQLite generation log, settings dedup, stats
file-hasher.ts # SHA256 hashing of .safetensors with cache
civitai-lookup.ts # CivitAI API lookup by content hash
workflow-settings-extractor.ts # Extract settings from workflow JSON
process-control.ts # Stop, start, restart ComfyUI process
registry-client.ts # ComfyUI Registry API
skill-generator.ts # Generate node pack skill docs
tools/ # MCP tool registration (one file per group)
workflow-execute.ts # enqueue_workflow, get_system_stats
workflow-visualize.ts # visualize_workflow, mermaid_to_workflow
workflow-compose.ts # create_workflow, modify_workflow, get_node_info
workflow-validate.ts # validate_workflow
workflow-library.ts # list_workflows, get_workflow, strip_workflow, slice_workflow, save_workflow
image-management.ts # upload_image, workflow_from_image, list_output_images
model-management.ts # search_models, download_model, list_local_models
memory-management.ts # clear_vram, get_embeddings
registry-search.ts # search_custom_nodes, get_node_pack_details
skill-generator.ts # generate_node_skill
generation-tracker.ts # suggest_settings, generation_stats
diagnostics.ts # get_logs, get_history
process-control.ts # stop_comfyui, start_comfyui, restart_comfyui
index.ts # Registers all tool groups
utils/
errors.ts # Custom error hierarchy with MCP integration
logger.ts # stderr-only logging (safe for stdio transport)
image.ts # Base64 encoding utilities
plugin/
.claude-plugin/ # Plugin manifest
.mcp.json # MCP server config for plugin
commands/ # Slash commands
gen.md # /comfy:gen — image generation
viz.md # /comfy:viz — workflow visualization
node-skill.md # /comfy:node-skill — skill generation
debug.md # /comfy:debug — failure diagnosis
batch.md # /comfy:batch — parameter sweeps
convert.md # /comfy:convert — format conversion
install.md # /comfy:install — node pack installation
gallery.md # /comfy:gallery — output browser
compare.md # /comfy:compare — workflow diff
recipe.md # /comfy:recipe — multi-step pipelines
skills/ # Knowledge bases
comfyui-core/ # Workflow format, node types, pipeline patterns
prompt-engineering/ # CLIP syntax, model-specific prompting
troubleshooting/ # Error catalog with patterns and fixes
model-compatibility/ # Compatibility matrix per model family
agents/ # Autonomous agents
explorer.md # Research custom node packs, generate skills
debugger.md # Diagnose workflow failures
optimizer.md # Analyze and optimize workflows
hooks/ # Pre/post tool-use hooks
hooks.json # Hook configuration
vram-check.mjs # VRAM watchdog before execution
save-warning.mjs # Save prompt before stop/restart
job-complete-notify.mjs # Job completion notification via temp files
scripts/ # Background scripts
monitor-progress.mjs # Real-time WebSocket progress monitor
Troubleshooting
"ComfyUI not detected on ports 8188, 8000"
Make sure ComfyUI is running. The Desktop app uses port 8000 by default; the CLI uses 8188. Set COMFYUI_PORT if you're using a custom port.
"COMFYUI_PATH is not configured"
The auto-detection couldn't find your ComfyUI data directory. Set COMFYUI_PATH to the directory containing your models/ folder (e.g., ~/Documents/ComfyUI).
"Multiple ComfyUI installations detected"
This is informational — the server uses the first one found. Set COMFYUI_PATH to pick a specific installation.
Model downloads fail
For HuggingFace gated models, set HUGGINGFACE_TOKEN. For CivitAI, set CIVITAI_API_TOKEN.
Workflow execution errors
Use /comfy:debug to automatically diagnose failures. Or use get_history / get_logs directly to see detailed error messages including Python tracebacks from ComfyUI.
Out of memory (OOM)
Use clear_vram to free GPU memory before running large workflows. The VRAM watchdog hook will warn you automatically if memory is critically low. See the troubleshooting skill for model-specific VRAM estimates.
Missing custom nodes
Use /comfy:install <pack> to install missing node packs from the registry. The debug command will detect and suggest missing packs automatically.
Contributing
Contributions are welcome! See CONTRIBUTING.md for the dev setup, project conventions, how to add an MCP tool, and the release process.
Quick version: fork → branch (feat/my-feature) → make changes (ensure npm run build and
npm test pass; run npm run docs:gen if you touched tools) → open a PR.
Maintainer
Built and maintained by @artokun — a regular contributor across the Comfy-Org ecosystem:
- Comfy-Org/ComfyUI_frontend — 10 merged PRs, mostly on the v2 graph renderer: subgraph rendering, promoted-widget plumbing, viewport persistence, with backports across
cloud/1.41,cloud/1.42,core/1.41, andcore/1.42. - Comfy-Org/ComfyUI (core) — crash fixes in the Python backend's video/audio save path (#12683, #12550).
Comfy-Org folks (or anyone hiring around the ComfyUI ecosystem): I'd genuinely love to chat — art.longbottom.jr@gmail.com.
License
MIT — see LICENSE for details.
Changelog
See CHANGELOG.md for the full, structured release history.