I craft unique cereal names, stories, and ridiculously cute Cereal Baby images.

comfyui-mcp-server
lightweight Python-based MCP (Model Context Protocol) server for local ComfyUI
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ComfyUI MCP Server
A lightweight Python-based MCP (Model Context Protocol) server that interfaces with a local ComfyUI instance to generate images programmatically via AI agent requests.
Overview
This project enables AI agents to send image generation requests to ComfyUI using the MCP protocol over WebSocket. It supports:
- Flexible workflow selection (e.g.,
basic_api_test.json
). - Dynamic parameters:
prompt
,width
,height
, andmodel
. - Returns image URLs served by ComfyUI.
Prerequisites
- Python 3.10+
-
ComfyUI: Installed and running locally (e.g., on
localhost:8188
). -
Dependencies:
requests
,websockets
,mcp
(install via pip).
Setup
-
Clone the Repository: git clone
cd comfyui-mcp-server -
Install Dependencies:
pip install requests websockets mcp
-
Start ComfyUI:
- Install ComfyUI (see ComfyUI docs).
- Run it on port 8188:
cd <ComfyUI_dir> python main.py --port 8188
- Prepare Workflows:
- Place API-format workflow files (e.g.,
basic_api_test.json
) in theworkflows/
directory. - Export workflows from ComfyUI’s UI with “Save (API Format)” (enable dev mode in settings).
Usage
- Run the MCP Server: python server.py
- Listens on
ws://localhost:9000
.
- Test with the Client: python client.py
- Sends a sample request:
"a dog wearing sunglasses"
with512x512
usingsd_xl_base_1.0.safetensors
. - Output example:
Response from server: { "image_url": "http://localhost:8188/view?filename=ComfyUI_00001_.png&subfolder=&type=output" }
- Custom Requests:
- Modify
client.py
’spayload
to changeprompt
,width
,height
,workflow_id
, ormodel
. - Example:
"params": json.dumps({ "prompt": "a cat in space", "width": 768, "height": 768, "workflow_id": "basic_api_test", "model": "v1-5-pruned-emaonly.ckpt" })
Project Structure
-
server.py
: MCP server with WebSocket transport and lifecycle support. -
comfyui_client.py
: Interfaces with ComfyUI’s API, handles workflow queuing. -
client.py
: Test client for sending MCP requests. -
workflows/
: Directory for API-format workflow JSON files.
Notes
- Ensure your chosen
model
(e.g.,v1-5-pruned-emaonly.ckpt
) exists in<ComfyUI_dir>/models/checkpoints/
. - The MCP SDK lacks native WebSocket transport; this uses a custom implementation.
- For custom workflows, adjust node IDs in
comfyui_client.py
’sDEFAULT_MAPPING
if needed.
Contributing
Feel free to submit issues or PRs to enhance flexibility (e.g., dynamic node mapping, progress streaming).
License
Apache License
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Reviews

user_gLoTVYp3
I've recently watched the tutorial video by TahaBakhtari on creating an MCP server, and it was incredibly helpful! The instructions were clear and easy to follow, which made the whole process smooth. Highly recommended for anyone looking to set up their own server. You can check it out at: https://mcp.so/server/TorobjoMCP/TahaBakhtari.