Fm MCP Comfyui Bridge

@rerofumi

Basic information

About Fm MCP Comfyui Bridge

LLM MCP server for image generation with ComfyUI

Fm MCP Comfyui Bridge config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "fm-mcp-comfyui-bridge": {
      "command": "uv",
      "args": [
        "pip",
        "install",
        "-e",
        "."
      ]
    }
  }
}

Fm MCP Comfyui Bridge tools

Tool list not available yet

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We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is fm-mcp-comfyui-bridge?

fm-mcp-comfyui-bridge is an MCP server implementation that provides image generation, captioning, and tag parsing by accessing the ComfyUI API. It is designed for developers using AI agent tools who need to interact with a local ComfyUI instance.

How to use fm-mcp-comfyui-bridge?

Install using uv (pip install -e .), then configure the MCP client with the command uv --directory <path> run fm-mcp-comfyui-bridge. Set the ComfyUI endpoint (default http://localhost:8188), create a config.yaml for checkpoint and LoRA settings, and an ollama.yaml for vision model. Use the provided tools generate_picture, get_picture, get_caption, and get_tag via the MCP interface.

Key features of fm-mcp-comfyui-bridge

Image generation using ComfyUI
Caption generation for generated images
Tag analysis (WD1.4) for generated images
Simple setup and launch with uv
Provides API endpoints as an MCP server

Use cases of fm-mcp-comfyui-bridge

Generate images from text prompts via ComfyUI
Retrieve PNG binary data of generated images
Obtain textual captions of generated images
Analyze generated images for WD1.4 tags

Frequently asked questions

What are the system requirements?

Python 3.13+, a locally running ComfyUI (default http://localhost:8188), the `uv` package manager, and a locally running ollama with a vision model for captioning.

How do I install and set up the server?

Clone the repository, run `uv pip install -e .`, then configure your MCP client with the command `uv --directory <path> run fm-mcp-comfyui-bridge`. Optionally copy the sample config file and edit `config.yaml` for your model and LoRA settings.

What tools does the server provide?

Four tools: `generate_picture` (generate image from prompt), `get_picture` (get PNG binary), `get_caption` (get text caption), and `get_tag` (get WD1.4 tags). API resources include `info://about`, `help://tools`, and `docs://{topic}`.

How do I use a custom workflow?

Place an API-format workflow JSON in `src/fm_mcp_comfyui_bridge/config/workflow/` and create a `custom.yaml` in the config directory. If `custom.yaml` exists, the custom workflow runs; otherwise the default workflow is used.

Where does the WD1.4 tag model come from?

The tag analysis part uses source code and model data from SmilingWolf’s wd-tagger. The model data is downloaded on first execution.

Comments

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