Model Registry

Community

artokun

model-registry

Curated download URLs and target directories, organized by family (Flux, WAN, LTX, Qwen, Z-Image, SD15/SDXL), for every model the comfyui-mcp skills reference, covering checkpoints, VAEs, text encoders, and LoRAs. Use when downloading models with download_model (action:"download" / action:"download_civitai"), when a workflow fails with a missing-model error, or when setting up a new machine.

Overview

Publisher	artokun
Repository	`comfyui-mcp`
Skill name	`model-registry`
Stars	811
Forks	137
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by artokun on GitHub. Read the source before you install it.

Installation

Install the Model Registry AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/artokun/comfyui-mcp/tree/main/plugin/skills/model-registry
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/artokun/comfyui-mcp.git /tmp/comfyui-mcp
mkdir -p .claude/skills
cp -r /tmp/comfyui-mcp/plugin/skills/model-registry .claude/skills/model-registry

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Model Registry in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Model Registry on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Model Registry is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Model Registry

One table per family: filename → source URL → target subdir under <COMFYUI>/models/. Use with download_model({ action: "download", url, target_subfolder, filename }). This registry grows with every release. If a model you need is missing, use action:"search" (HuggingFace) or action:"download_civitai" and consider contributing the row.

Quant column (kitchen). Filenames in this registry are mostly bf16 / fp8. NVFP4 and MXFP8 siblings, when a vendor publishes them, are the same stem with nvfp4 / mxfp8 in the name and belong in diffusion_models/ too. kitchen action:"assess" only offers an NVFP4 swap when that sibling is already listed locally — it does not guess a URL from the filename. Blackwell (SM ≥ 10.0) is the GPU that can run NVFP4 / MXFP8 compute.

Conventions

HF "resolve" URLs download directly: https://huggingface.co/<repo>/resolve/main/<path>
🔒 = gated repo, needs HUGGINGFACE_TOKEN (accept the license on the HF page first)
CivitAI model-page URLs need download_model action:"download_civitai" (resolves version → file); raw civitai.com/api/download/... URLs work with action:"download" + CIVITAI_API_TOKEN
Always verify the exact filename a workflow's loader expects. The model-compatibility skill covers which VAE/CLIP pairs with which architecture

Shared VAEs & text encoders (download these once)

File	Source	Target
`ae.safetensors` (Flux/Z-Image VAE)	`huggingface.co/black-forest-labs/FLUX.1-schnell/resolve/main/ae.safetensors` (Apache, not gated)	`vae/`
`vae-ft-mse-840000-ema-pruned.safetensors` (SD1.5 VAE)	`huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.safetensors`	`vae/`
`clip_l.safetensors`	`huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors`	`text_encoders/`
`t5xxl_fp8_e4m3fn.safetensors`	`huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp8_e4m3fn.safetensors`	`text_encoders/`
`umt5_xxl_fp8_e4m3fn_scaled.safetensors` (WAN)	`huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors`	`text_encoders/`

Flux (see `flux-txt2img` skill for workflows)

File	Source	Target
`flux1-dev.safetensors` 🔒	`huggingface.co/black-forest-labs/FLUX.1-dev`	`diffusion_models/`
`flux1-schnell.safetensors`	`huggingface.co/black-forest-labs/FLUX.1-schnell/resolve/main/flux1-schnell.safetensors`	`diffusion_models/`
`flux2-vae.safetensors` (Flux 2 Klein)	`huggingface.co/Comfy-Org/flux2-klein` — check repo for current path	`vae/`

WAN 2.x video (see `wan-t2v-video` / `wan-flf-video` skills)

Comfy-Org repackages everything: huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged under split_files/.

File	Path in repo	Target
`wan2.2_i2v_high_noise_14B_fp8_scaled.safetensors`	`split_files/diffusion_models/`	`diffusion_models/`
`wan2.2_i2v_low_noise_14B_fp8_scaled.safetensors`	`split_files/diffusion_models/`	`diffusion_models/`
`wan_2.1_vae.safetensors`	`split_files/vae/`	`vae/`
`wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors`	`split_files/loras/`	`loras/`
`wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors`	`split_files/loras/`	`loras/`
Magical-morph I2V LoRAs (high/low)	`huggingface.co/NikolaSigmoid/wan2.2-i2v-loras-magical-morph`	`loras/`
SkinMorph Redmond I2V 14B	`civitai.com/models/2210162` (use `action:"download_civitai"`)	`loras/`

LTX-2 19B video (see `ltxv2-video` skill)

File	Source	Target
`ltx-2-19b-distilled.safetensors`	`huggingface.co/Lightricks/LTX-2` — check repo for the bf16 distilled path	`checkpoints/`
`gemma_3_12B_it_fp4_mixed.safetensors`	`huggingface.co/Comfy-Org` LTX repackage	`text_encoders/`
`ltx-2-spatial-upscaler-x2-1.0.safetensors`	`huggingface.co/Lightricks/LTX-2`	`upscale_models/`
Camera-control LoRAs (`dolly-left`, distilled-384)	`huggingface.co/Lightricks/LTX-2` LoRA dir	`loras/`

Qwen-Image (see `qwen-txt2img` / `qwen-image-edit` skills)

File	Source	Target
`qwen_image_fp8_e4m3fn.safetensors`	`huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/diffusion_models/qwen_image_fp8_e4m3fn.safetensors`	`diffusion_models/`
`qwen_2.5_vl_7b_fp8_scaled.safetensors`	same repo, `split_files/text_encoders/`	`text_encoders/`
`qwen_image_vae.safetensors`	same repo, `split_files/vae/`	`vae/`
`qwen_image_edit_2511_bf16.safetensors`	`huggingface.co/Comfy-Org/Qwen-Image-Edit_ComfyUI` — check repo	`diffusion_models/`
Qwen-Image 2512 Lightning LoRA	`huggingface.co/lightx2v/Qwen-Image-2512-Lightning`	`loras/`
Qwen-Image-Edit 2511 Lightning LoRA	`huggingface.co/lightx2v/Qwen-Image-Edit-2511-Lightning`	`loras/`
Qwen-Image 2512 Turbo LoRA	`huggingface.co/Wuli-art/Qwen-Image-2512-Turbo-LoRA`	`loras/`

MiniMax H3 video (see `minimax-h3-video` skill)

Comfy-Org INT8 pack: huggingface.co/Comfy-Org/MiniMax-H3. Local weights are under the MiniMax H3 Community License (territory-restricted). Prefer the filenames the Comfy-Org templates already name.

File	Source	Target
`minimax_h3_fl2va_pruned_int8_convrot.safetensors`	`huggingface.co/Comfy-Org/MiniMax-H3/resolve/main/diffusion_models/minimax_h3_fl2va_pruned_int8_convrot.safetensors`	`diffusion_models/`
`minimax_h3_ref2va_pruned_int8_convrot.safetensors`	same repo, `diffusion_models/`	`diffusion_models/`
`qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors`	same repo, `text_encoders/`	`text_encoders/`
`minimax_h3_video_vae_fp16.safetensors`	same repo, `vae/`	`vae/`
`minimax_h3_audio_vae_fp32.safetensors`	same repo, `vae/`	`vae/`
`minimax_h3_fl2v_turbo_8step_v1.0_comfyui_bf16.safetensors`	`huggingface.co/lightx2v/Minimax-h3-Turbo/resolve/main/minimax_h3_fl2v_turbo_8step_v1.0_comfyui_bf16.safetensors`	`loras/`
`minimax_h3_fl2v_turbo_4step_v1.0_768p_comfyui_bf16.safetensors`	`huggingface.co/Comfy-Org/MiniMax-H3/resolve/main/loras/minimax_h3_fl2v_turbo_4step_v1.0_768p_comfyui_bf16.safetensors`	`loras/`

Z-Image (see `z-image-txt2img` skill)

File	Source	Target
`z_image_turbo_bf16.safetensors`	`huggingface.co/Comfy-Org/z_image_turbo` — check repo for split_files path	`diffusion_models/`
`z_image_base_bf16.safetensors`	same family repo	`diffusion_models/`
`qwen_3_4b.safetensors` (Z-Image text encoder)	Comfy-Org repackage, `split_files/text_encoders/`	`text_encoders/`

SDXL / SD1.5 community checkpoints (CivitAI)

Use download_model({ action: "download_civitai", model_id }). It resolves the latest version and handles auth:

Model	CivitAI
RedCraft RedZ ImageDX	`civitai.com/models/958009`
Qwen Ultimate Realism v1.1	`civitai.com/models/2027494`
Copax Timeless	`civitai.com/models/copaxTimeless` (search by name)

Failure modes

404 on an HF resolve URL. The repo restructured. Open the repo page, find the file under "Files", and rebuild the resolve URL.
401/403. Gated repo. Set HUGGINGFACE_TOKEN after accepting the license, or CIVITAI_API_TOKEN for early-access CivitAI files.
Wrong dropdown after download. The file landed in the wrong models/ subdir; check the Target column and model-compatibility.
Downloads resume on retry (HTTP Range), so re-run the same download_model call after a network drop.

Sources

Official: Hugging Face resolve-URL convention https://huggingface.co//resolve/main/; kitchen NVFP4/MXFP8 hardware gates in ComfyUI comfy/model_management.py and quant metadata in comfy/quant_ops.py.
Empirical: the curated list and Civitai notes are ours, not a vendor catalog.

Frequently asked questions

What does the Model Registry AI skill do?

Why use Model Registry on TypingMind?

Because you install it once and use it with any model. Model Registry is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Model Registry in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/artokun/comfyui-mcp/tree/main/plugin/skills/model-registry. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Model Registry?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Model Registry?

As many as you like. As long as a model supports skills, you can use Model Registry with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Model Registry AI skill free?

Yes. It is published on GitHub by artokun under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Model Registry

Shared VAEs & text encoders (download these once)

Flux (see flux-txt2img skill for workflows)

WAN 2.x video (see wan-t2v-video / wan-flf-video skills)

LTX-2 19B video (see ltxv2-video skill)

Qwen-Image (see qwen-txt2img / qwen-image-edit skills)

MiniMax H3 video (see minimax-h3-video skill)

Z-Image (see z-image-txt2img skill)

SDXL / SD1.5 community checkpoints (CivitAI)

Failure modes

Sources

Frequently asked questions

Related AI Skills

Set up your own AI workspace now

Flux (see `flux-txt2img` skill for workflows)

WAN 2.x video (see `wan-t2v-video` / `wan-flf-video` skills)

LTX-2 19B video (see `ltxv2-video` skill)

Qwen-Image (see `qwen-txt2img` / `qwen-image-edit` skills)

MiniMax H3 video (see `minimax-h3-video` skill)

Z-Image (see `z-image-txt2img` skill)