iflow-mcp_joenorton-comfyui-mcp-server

# ComfyUI MCP Server > Generate and refine AI images/audio/video through natural conversation A lightweight MCP (Model Context Protocol) server that lets AI agents generate and iteratively refine images, audio, and video using a local ComfyUI instance. You run the server, connect a client, and issue tool calls. Everything else is optional depth. --- ## Quick Start (2–3 minutes) This proves everything is working. ### 1) Clone and set up ```bash git clone https://github.com/joenorton/comfyui-mcp-server.git cd comfyui-mcp-server pip install -r requirements.txt ``` ### 2) Start ComfyUI Make sure ComfyUI is installed and running locally. ```bash cd <ComfyUI_dir> python main.py --port 8188 ``` ### 3) Run the MCP server From the repository directory: ```bash python server.py ``` The server listens at: ``` http://127.0.0.1:9000/mcp ``` ### 4) Verify it works (no AI client required) Run the included test client: ```bash # Use default prompt python test_client.py # Or provide your own prompt python test_client.py -p "a beautiful sunset over mountains" python test_client.py --prompt "a cat on a mat" ``` `test_client.py` will: * connect to the MCP server * list available tools * fetch and display server defaults (width, height, steps, model, etc.) * run `generate_image` with your prompt (or a default) * automatically use server defaults for all other parameters * print the resulting asset information If this step succeeds, the system is working. **Note:** The test client respects server defaults configured via config files, environment variables, or `set_defaults` calls. Only the `prompt` parameter is required; all other parameters use server defaults automatically. That’s it. --- ## Use with an AI Agent (Cursor / Claude / n8n) Once the server is running, you can connect it to an AI client. Create a project-scoped `.mcp.json` file: ```json { "mcpServers": { "comfyui-mcp-server": { "type": "streamable-http", "url": "http://127.0.0…