comfyui-mcp

MCP server + Claude Code plugin for ComfyUI — execute workflows, generate images, visualize pipelines, manage models, control VRAM, and explore custom nodes, all from your AI coding assistant.

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

31 MCP tools | 10 slash commands | 4 knowledge skills | 3 autonomous agents | 3 hooks

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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.

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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

claude plugin install comfyui-mcp

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

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.

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MCP Tools

31 tools organized into 13 categories:

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)
cancel_job	Interrupt the currently running job
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
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
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 from the output directory, sorted newest-first

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

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).

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Examples

Generate an image

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

Claude will:

1. Check installed checkpoints (download one if needed)
2. Build a txt2img workflow with your prompt
3. Execute it on ComfyUI
4. 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

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Configuration

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

Variable	Default	Description
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
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)
LOG_LEVEL	info	Logging verbosity: debug, info, warn, error

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 ~/Documents and ~/My Documents for any directory containing "ComfyUI"

Set COMFYUI_PATH to skip detection and use an explicit path.

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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.

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Development

Prerequisites

• Node.js >= 22.0.0
• ComfyUI running locally

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

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
    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, 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

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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.

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Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feat/my-feature)
3. Make your changes and ensure npm run lint passes
4. Submit a pull request

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License

MIT — see LICENSE for details.