comfyui-mcp
Version:
Local-first, agent-native control plane for ComfyUI — MCP server + autonomous sidebar agent that drives your live graph in natural language on ANY LLM: Claude/ChatGPT/Gemini on your subscription (no API key), free local models via Ollama (fully offline),
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YAML
name: z-image-turbo-txt2img
display_name: Z-Image-Turbo — Text to Image
family: z-image
kind: txt2img
description: >-
Z-Image-Turbo (Alibaba Tongyi, distilled S3-DiT) text-to-image — fast, sharp
results in ~8-14 steps at cfg 1. Uses a Qwen text encoder (not CLIP/T5).
Single-purpose txt2img graph sliced from the z-image-turbo monolith (one
pipeline, no group toggles), with optional film-grain / laplacian-sharpen
post-processing and seed-variance.
vram: "<8GB"
workflow: workflow.json
skill: z-image-txt2img
launch_args: []
sources:
model: https://huggingface.co/Comfy-Org/z_image_turbo
mirror: https://huggingface.co/Aitrepreneur/FLX
notes:
- Run the generated installer from your ComfyUI root (folder with custom_nodes/
and models/).
- Sliced + un-bypassed from the monolith's "Z-IMAGE TURBO TEXT TO IMAGE".
- The z-image VAE is saved as z-image-ae.safetensors (its weights differ from
Flux's ae.safetensors despite the same size).
post_install:
- Restart ComfyUI (or ComfyUI-Manager -> Install missing custom nodes for any
node Python deps).
- Load workflow.json.