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

Lalanikarim_comfy-MCP-Server
Miroir dehttps: //github.com/lalanikarim/comfy-mcp-server
0
Github Watches
1
Github Forks
1
Github Stars
Comfy MCP Server
A server using FastMCP framework to generate images based on prompts via a remote Comfy server.
Overview
This script sets up a server using the FastMCP framework to generate images based on prompts using a specified workflow. It interacts with a remote Comfy server to submit prompts and retrieve generated images.
Prerequisites
- Python 3.x installed.
- Required packages:
mcp
,json
,urllib
,time
,os
. - Workflow file exported from Comfy UI. This code includes a sample
Flux-Dev-ComfyUI-Workflow.json
which is only used here as reference. You will need to export from your workflow and set the environment variables accordingly.
You can install the required packages using pip:
pip install "mcp[cli]"
Configuration
Set the following environment variables:
-
COMFY_URL
to point to your Comfy server URL. -
COMFY_WORKFLOW_JSON_FILE
to point to the absolute path of the API export json file for the comfyui workflow. -
PROMPT_NODE_ID
to the id of the text prompt node. -
OUTPUT_NODE_ID
to the id of the output node with the final image.
Example:
export COMFY_URL=http://your-comfy-server-url:port
export COMFY_WORKFLOW_JSON_FILE=/path/to/the/comfyui_workflow_export.json
export PROMPT_NODE_ID=6 # use the correct node id here
export OUTPUT_NODE_ID=9 # use the correct node id here
Usage
Run the script directly:
python comfy-mcp-server.py
The server will start and listen for requests to generate images based on the provided prompts.
Functionality
generate_image(prompt: str, ctx: Context) -> Image | str
This function generates an image using a specified prompt. It follows these steps:
- Checks if all the environment variable are set.
- Loads a prompt template from a JSON file.
- Submits the prompt to the Comfy server.
- Polls the server for the status of the prompt processing.
- Retrieves and returns the generated image once it's ready.
Dependencies
-
mcp
: For setting up the FastMCP server. -
json
: For handling JSON data. -
urllib
: For making HTTP requests. -
time
: For adding delays in polling. -
os
: For accessing environment variables.
License
This project is licensed under the MIT License - see the LICENSE file for details.
相关推荐
I find academic articles and books for research and literature reviews.
Evaluator for marketplace product descriptions, checks for relevancy and keyword stuffing.
Confidential guide on numerology and astrology, based of GG33 Public information
Emulating Dr. Jordan B. Peterson's style in providing life advice and insights.
Your go-to expert in the Rust ecosystem, specializing in precise code interpretation, up-to-date crate version checking, and in-depth source code analysis. I offer accurate, context-aware insights for all your Rust programming questions.
Advanced software engineer GPT that excels through nailing the basics.
This GPT assists in finding a top-rated business CPA - local or virtual. We account for their qualifications, experience, testimonials and reviews. Business operators provide a short description of your business, services wanted, and city or state.
Découvrez la collection la plus complète et la plus à jour de serveurs MCP sur le marché. Ce référentiel sert de centre centralisé, offrant un vaste catalogue de serveurs MCP open-source et propriétaires, avec des fonctionnalités, des liens de documentation et des contributeurs.
L'application tout-en-un desktop et Docker AI avec chiffon intégré, agents AI, constructeur d'agent sans code, compatibilité MCP, etc.
Manipulation basée sur Micropython I2C de l'exposition GPIO de la série MCP, dérivée d'Adafruit_MCP230XX
Plateforme d'automatisation de workflow à code équitable avec des capacités d'IA natives. Combinez le bâtiment visuel avec du code personnalisé, de l'auto-hôte ou du cloud, 400+ intégrations.
🧑🚀 全世界最好的 LLM 资料总结 (数据处理、模型训练、模型部署、 O1 模型、 MCP 、小语言模型、视觉语言模型) | Résumé des meilleures ressources LLM du monde.
Une liste organisée des serveurs de protocole de contexte de modèle (MCP)
Reviews

user_pzbukaGV
As a dedicated user of the lalanikarim_comfy-mcp-server by MCP-Mirror, I find this server solution incredibly efficient and user-friendly. The seamless integration and the ease of setup through the provided GitHub link (https://github.com/MCP-Mirror/lalanikarim_comfy-mcp-server) have significantly enhanced my workflow. The welcoming information and straightforward start URL make deployment quick and headache-free. Overall, it's an invaluable tool for MCP applications.