ComfyUI MCP Server

1. Overview

• A server implementation for integrating ComfyUI with MCP.
• ⚠️ IMPORTANT: This server requires a running ComfyUI server.
  • You must either host your own ComfyUI server,
  • or have access to an existing ComfyUI server address.

---

2. Debugging

### 2.1 ComfyUI Debugging

bash python src/test_comfyui.py

### 2.2 MCP Debugging

bash mcp dev src/server.py

---

3. Installation and Configuration

### 3.1 ComfyUI Configuration

• Edit src/.env to set ComfyUI host and port:

  env COMFYUI_HOST=localhost COMFYUI_PORT=8188

### 3.2 Adding Custom Workflows

• To add new tools, place your workflow JSON files in the workflows directory and declare them as new tools in the system.

---

4. Built-in Tools

• text_to_image

  • Returns only the URL of the generated image.
  • To get the actual image:
    • Use the download_image tool, or
    • Access the URL directly in your browser.

• download_image

  • Downloads images generated by other tools (like text_to_image) using the image URL.

• run_workflow_with_file

  • Run a workflow by providing the path to a workflow JSON file.

    ```

    You should ask to agent like this.

    Run comfyui workflow with text_to_image.json ```

  • example image of CursorAI

• run_workflow_with_json

  • Run a workflow by providing the workflow JSON data directly.

    ```

    You should ask to agent like this.

    Run comfyui workflow with this { "3": { "inputs": { "seed": 156680208700286, "steps": 20, ... (workflow JSON example) } ```

---

5. How to Run

### 5.1 Using UV (Recommended)

• Example mcp.json:

  json { "mcpServers": { "comfyui": { "command": "uv", "args": [ "--directory", "PATH/MCP/comfyui", "run", "--with", "mcp", "--with", "websocket-client", "--with", "python-dotenv", "mcp", "run", "src/server.py:mcp" ] } } }

### 5.2 Using Docker

• Downloading images to a local folder with download_image may be difficult since the Docker container does not share the host filesystem.
• When using Docker, consider:
  1. Set RETURN_URL=false in .env to receive image data as bytes.
  2. Set COMFYUI_HOST in .env to the appropriate address (e.g., host.docker.internal or your server's IP).
  3. Note: Large image payloads may exceed response limits when using binary data.

#### 5.2.1 Build Docker Image

bash # First build image docker image build -t mcp/comfyui .

json { "mcpServers": { "comfyui": { "command": "docker", "args": [ "run", "-i", "--rm", "-p", "3001:3000", "mcp/comfyui" ] } } }

#### 5.2.2 Using Existing Images

Also you can use prebuilt image.

json { "mcpServers": { "comfyui": { "command": "docker", "args": [ "run", "-i", "--rm", "-p", "3001:3000", "overseer66/mcp-comfyui" ] } } }

#### 5.2.3 Using SSE Transport

1. Run the SSE server with Docker:

   bash docker run -i --rm -p 8001:8000 overseer66/mcp-comfyui-sse

2. Configure mcp.json (change localhost to your IP or domain if needed):

   json { "mcpServers": { "comfyui": { "url": "http://localhost:8001/sse" } } }

NOTE: When adding new workflows as tools, you need to rebuild and redeploy the Docker images to make them available.

---