ComfyMCP

Give Claude the ability to generate images with ComfyUI. Just ask for what you want in natural language.

You: "Generate an image of a robot painting a sunset"

Claude: I'll create that image for you.
        [builds 7-node workflow, executes it]
        Done! Generated robot_painting_00001.png in 2.3 seconds.

What You Can Ask

Once installed, Claude can handle requests like:

Image Generation

• "Generate an image of a cat astronaut floating in space"
• "Create a 1024x1024 fantasy landscape using SDXL"
• "Make a portrait with negative prompt 'blurry, low quality'"

Model & System Info

• "What checkpoint models do I have?"
• "Show me the available samplers"
• "What's my GPU memory usage?"

Workflow Control

• "Use 30 steps instead of 20 for better quality"
• "Generate 4 variations with different seeds"
• "What's the status of my last generation?"

Claude handles all the complexity—discovering nodes, building connections, validating the workflow, and monitoring execution.

How It Works

When you ask Claude to generate an image, it builds a complete ComfyUI workflow:

[1] CheckpointLoaderSimple ─────────────────────────────┐
     ├── MODEL ──────────────────────────────────────────┤
     ├── CLIP ───┬──→ [3] CLIPTextEncode (positive) ────┤
     │           └──→ [4] CLIPTextEncode (negative) ────┤
     └── VAE ────────────────────────────────────────────┤
                                                         ▼
[2] EmptyLatentImage ──────────────────────────→ [5] KSampler
                                                         │
                                                         ▼
                                                 [6] VAEDecode
                                                         │
                                                         ▼
                                                 [7] SaveImage

This happens automatically. Claude:

1. Discovers available nodes and their inputs/outputs
2. Builds the workflow with proper connections
3. Validates everything before execution
4. Queues the job and monitors completion
5. Reports the output filename

Installation

Prerequisites

• ComfyUI running (default: localhost:8188)
• uv package manager

# Install uv if needed
curl -LsSf https://astral.sh/uv/install.sh | sh

Claude Code (CLI)

claude mcp add comfyui \
  --transport stdio \
  --env COMFYUI_HOST=127.0.0.1 \
  --env COMFYUI_PORT=8188 \
  -- uvx --from git+https://github.com/hernantech/comfymcp comfymcp

Claude Desktop

Add to your config file:

• Linux: ~/.config/claude/claude_desktop_config.json
• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "comfyui": {
      "command": "uvx",
      "args": ["--from", "git+https://github.com/hernantech/comfymcp", "comfymcp"],
      "env": {
        "COMFYUI_HOST": "127.0.0.1",
        "COMFYUI_PORT": "8188"
      }
    }
  }
}

Verify Installation

Ask Claude: "Check if ComfyUI is connected"

You should see confirmation that the server is online with GPU info.

Configuration

Environment Variable	Description	Default
COMFYUI_HOST	ComfyUI server address	127.0.0.1
COMFYUI_PORT	ComfyUI server port	8188
COMFYUI_API_KEY	API key (if required)	None

For remote ComfyUI servers, update the host:

claude mcp add comfyui \
  --env COMFYUI_HOST=192.168.1.100 \
  ...

---

Reference

Available MCP Tools

<details> <summary><strong>Workflow Execution</strong></summary>

Tool	Description
queue_prompt	Submit a workflow for execution
get_queue_status	Check running/pending jobs
get_job_status	Get status of a specific job
get_history	View execution history
interrupt_execution	Stop current generation
clear_queue	Clear pending jobs

</details>

<details> <summary><strong>Workflow Building</strong></summary>

Tool	Description
create_workflow	Start a new workflow session
add_node	Add a node with inputs
build_workflow	Finalize and validate
validate_workflow	Check for errors
list_nodes	Search available nodes
get_node_info	Get node specifications
refresh_nodes	Reload node definitions

</details>

<details> <summary><strong>Assets & Models</strong></summary>

Tool	Description
list_models	List checkpoints, LoRAs, VAEs, etc.
list_embeddings	List textual inversions
list_output_images	List generated images
get_image	Retrieve an image
upload_image	Upload for img2img

</details>

<details> <summary><strong>System</strong></summary>

Tool	Description
check_connection	Verify ComfyUI is reachable
get_system_stats	GPU memory, system info
free_memory	Unload models, clear cache
get_extensions	List installed extensions

</details>

MCP Resources

URI	Description
comfyui://nodes	All available nodes
comfyui://nodes/categories	Node categories
comfyui://nodes/{class_type}	Specific node definition
comfyui://outputs	Recent outputs
comfyui://images/{filename}	Retrieve image

---

Python API

For programmatic use outside of MCP:

from comfymcp.workflow import WorkflowBuilder

builder = WorkflowBuilder()

# Nodes return refs with named outputs
checkpoint = builder.add_node("CheckpointLoaderSimple",
    ckpt_name="sd_turbo.safetensors")

latent = builder.add_node("EmptyLatentImage",
    width=512, height=512, batch_size=1)

positive = builder.add_node("CLIPTextEncode",
    clip=checkpoint.CLIP,  # Named output connection
    text="a beautiful sunset")

negative = builder.add_node("CLIPTextEncode",
    clip=checkpoint.CLIP,
    text="ugly, blurry")

sampler = builder.add_node("KSampler",
    model=checkpoint.MODEL,
    positive=positive.CONDITIONING,
    negative=negative.CONDITIONING,
    latent_image=latent.LATENT,
    seed=42, steps=4, cfg=1.0,
    sampler_name="euler", scheduler="normal", denoise=1.0)

decode = builder.add_node("VAEDecode",
    samples=sampler.LATENT,
    vae=checkpoint.VAE)

builder.add_node("SaveImage",
    images=decode.IMAGE,
    filename_prefix="output")

workflow = builder.build()

Templates

from comfymcp.templates import Text2ImgTemplate, Img2ImgTemplate

# Text to image
txt2img = Text2ImgTemplate(
    checkpoint="sd_turbo.safetensors",
    positive_prompt="a majestic mountain",
    negative_prompt="ugly, blurry",
    width=512, height=512,
    steps=4, cfg=1.0
)
workflow = txt2img.build()

# Image to image
img2img = Img2ImgTemplate(
    checkpoint="sd_turbo.safetensors",
    image="input.png",
    positive_prompt="enhance details",
    denoise=0.6
)
workflow = img2img.build()

Direct Client Usage

from comfymcp.client import ComfyUIClient

async with ComfyUIClient(host="127.0.0.1", port=8188) as client:
    # Queue workflow
    result = await client.queue_prompt(workflow)

    # Check status
    history = await client.get_history(prompt_id=result.prompt_id)

    # List models
    checkpoints = await client.get_models("checkpoints")

---

Requirements

• Python 3.10+
• ComfyUI server running
• MCP-compatible client (Claude Code, Claude Desktop, Cursor, etc.)

License

MIT License - see LICENSE for details.