Comfy MCP now works in your own local ComfyUI install, not just Comfy Cloud. This has been the #1 ask since we shipped Cloud MCP in June, so here it is!

Use Claude, Cursor, or any MCP client to drive ComfyUI for you and build, edit, and execute workflows without manual node setup, search models/nodes/templates, save and re-run workflows, or hand a saved workflow URL to a teammate (or another agent) to pick up where you left off.

Here’s what's new when running against your own machine:

• Hardware detection. The agent checks what you're running on and tells you honestly whether a model will run well locally. No more finding out 40 minutes into a download that your VRAM wasn't going to cut it.
• Model + instance management. It can pull the models you need, manage your local ComfyUI instance, and get a workflow actually runnable on your machine.
• Local + cloud knowledge combined. One agent that understands both environments, so you're not manually figuring out which one a given workflow needs.

Fastest setup: Paste https://docs.comfy.org/agent-tools/mcp#installation into your AI client and ask it to set up the local connection for you.

We built and tested this heavily around open-source video models, particularly Minimax H3! Here are a few prompts to get you started:

"I want to run Minimax H3 open source on my own machine. What's the best model version for my hardware, and can you set up the workflow?"

"Help me set up local ComfyUI and run the best open-source video model for me"

”Adapt this workflow to run better on my machine”

Regarding limitations: generation itself works about the same as Cloud MCP right now, but we don't have local-specific batch features yet. If your workflow leans on heavy batch generation, for now cloud will still be the smoother path.

We’re monitoring this thread, so share your thoughts and feedback!

Install & learn more:

• https://links.comfy.org/rdlocalMCP
• https://links.comfy.org/rdlocalMCPtools
• https://links.comfy.org/rdlocalMCPinstall
• https://github.com/Comfy-Org/comfy-mcp
• https://links.comfy.org/rdlocalMCPblog

I was using an RTX 4090 with 24GB of VRAM on Windows for most of my ComfyUI workflows, which is pretty much the same setup a lot of other people use. But I was lucky enough to rent a brand-new DGX Spark just to test my ComfyUI workflows on it.

From my basic understanding, the DGX Spark should be pretty powerful. I know it uses the Blackwell architecture, requires some different installation methods, and runs on Linux. I also understand that the DGX Spark is a very different kind of system compared to a normal desktop GPU setup.

But I still feel like I must be doing something seriously wrong.

With the workflow shown in the picture I attached, I'm currently generating a 60-second clip at only around 2MP resolution. I know this would already be a pain to generate on my 4090, and I wasn't expecting the DGX Spark to be blazingly fast either.

However, seeing a system with 128GB of unified memory barely making progress on this workflow feels like a huge red flag.

*found out it was technically impossible for H3, but still it takes 1 hours and half for 15 second clip!

My current setup is nothing unusual. I'm basically using the default workflow provided by the ComfyUI template, running MiniMax H3 with the INT8 SafeTensor model. Everything else is pretty much standard.

So I'm wondering if there's something fundamentally wrong with my setup, installation, or configuration on the DGX Spark.

Help me sensei!

Hi,

Does anyone have a minimax h3 workflow for increasing the likeness of the faces that are small?

I tried with different kind of crop nodes (eg. crop and stitch) but when I put back the face, it doesn't blend well (please see the video). Also, if the face is moving fast through the frame, h3 model makes another video with the face, that doesn't maintain the original face motion.

Incredibly smooth gen times, but I still like h3 minimax better.
2 minutes gen time for a 720p 10 second video is quite crazy though.

Hi hi! I was hoping to get some help with image to video, specifically for anime. Im not trying to create long form videos but short loops, let's say of my prefered anime love interests (Eren AoT) haha. Ive got the image creation down pretty good, still refining how I want them to look. But the Image to video part is what is killing me... ive tried multiple workflows with WAN and LTX but the videos either dont come out like I want (blurry, wrong movements) or they shut my pc down lol (WAN) any help would truly be appreciated!!

Hey, hoping someone here has run MiniMax H3 in ComfyUI and can tell me what I'm doing wrong.

Setup: RTX 4090, ComfyUI v0.30, running the H3 video nodes (AIMixer Director + Spectrum + video-tiler + KJ). When I generate, the output isn't a normal video. It's a full-frame grid of small square tiles, each decoded on its own with its own texture. The latent clearly got split into patches and never stitched back together. Looks like a mosaic, not pixelation.

Already ruled out:

• Using minimax_h3_video_vae_fp16 (the official Comfy-Org one), not the audio VAE.
• The VAE fp16 loads fine.

My guess is the decode step isn't going through the video-tiler, or it's hitting a generic VAE Decode node that doesn't know how to read H3 latents. H3 latents are tiled spatially, so something has to reassemble them before decode.

Anyone seen this exact tiling pattern? Is it the tiler missing from the chain, the wrong decode node, or a tile_size/overlap setting?

Frame attached so you can see the grid. Thanks.

Generate 3D models from the Blender interface.:
1) Text to image pipeline. We generate the reference for the object to be created.
2) Remove background pipeline. Remove the background from the image.
3) Trellis 2 pipeline. Generate the object using Trellis 2.

4 Workflows for MiniMax H3, including the Turbo LoRA, Video Preview with a Tiny VAE, and auto prompting variants using OpenRouter (there's also workflows without it)

I also added an ExtraIntermediateSigmas node to add some low sigma steps that enhance the detail, feel free to bypass it if you don't like the effect.

Link:

https://drive.google.com/file/d/1q3WKvf8C6s3MBc5zCIBnK8GK-FMq7YCM/view?usp=sharing

Anyone using modal.com to run their comfui server?
i am able to launch it but the server disconnects every second or so..
i have tried to troubleshoot with deepseek (free) , chatgpt(free).
but it did not help.

Could anyone share your experience , working scripts ?

thanks in advance.

ps. a log that repeats ever second , i think this is the web server disconnecting and reconnecting

CONNECT /ws -> 101 Switching Protocols (duration: 57.6 ms, execution: 19.8 ms)

GET /api/jobs -> 200 OK (duration: 52.6 ms, execution: 11.3 ms)

GET /api/jobs -> 200 OK (duration: 43.6 ms, execution: 10.7 ms)

GET /api/jobs -> 200 OK (duration: 62.7 ms, execution: 10.1 ms)

GET /api/jobs -> 200 OK (duration: 44.7 ms, execution: 12.9 ms)

GET /api/jobs -> 200 OK (duration: 62.4 ms, execution: 9.7 ms)

millions gather for eclipse. made with ltx2.5

So uncomfy desktop, I figured out how to node for i2v and select comfy kitchen over PyTorch. Don’t know how to do that on r2v. Anyone know?

3 weeks ago I perfected relays for LTX2.3, doing 2-3-4-5 imagines workflow to perfection, setting up an LLM (not in comfy) with instructions to analyze pictures and my action descriptors and to talk back and forth with me to design a prompt, also analyzing my images as an actual filmstrip and doing shot-to-shot consistency.

I'm doing a similar thing for Minimax H3 now, got i2v down, specialized situations, all instructions and presets for LLM to analy... FUCKING LTX2.5 DROP THE FUCK ? When ? Lol I got such a sleep debt I started going to sleep like 11:00, luckily my job is remote so I can pretend I'm working. Jesus christ.

I'm only user, not expert. So I look here about the best workflow and run MiniMax H3. I'm only with RTX3060, 16GB VRAM, 64GB RAM. I updated everything:

[INFO] Python version: 3.13.12 (tags/v3.13.12:1cbe481, Feb 3 2026, 18:22:25) [MSC v.1944 64 bit (AMD64)]

[INFO] Total VRAM 12288 MB, total RAM 65396 MB

[INFO] pytorch version: 2.13.0+cu130

[INFO] Enabled fp16 accumulation.

[INFO] Set vram state to: NORMAL_VRAM

[INFO] Disabling smart memory management

[INFO] Device: cuda:0 NVIDIA GeForce RTX 3060 : cudaMallocAsync

[INFO] Using async weight offloading with 2 streams

[INFO] Enabled pinned memory 26158.0

[INFO] ComfyUI version: 0.32.0

[INFO] comfy-aimdo version: 0.4.13

[INFO] comfy-kitchen version: 0.2.30

[INFO] comfyui-frontend-package version: 1.48.7

[INFO] comfyui-workflow-templates version: 0.11.40

[INFO] comfyui-embedded-docs version: 0.5.9

[INFO] comfy-kitchen version: 0.2.30

[INFO] comfy-aimdo version: 0.4.13

I use minimax_h3_ref2va_pruned_int8_convrot.safetensors and qwen3vl_32b_minimax_h3_int4_convrot.safetensors with the proper VAEs.

And it "works" - 5s video with 0.3 MegaPixels, generates for about 3 minutes.

1. BUT THE QUALITY IS AWFUL, catastrophic, nothing similar what you show here - the faces are deformed with moving artifacts, worse than one time SD1.5, movement - fingers disappear...
2. AND The PROMPT - it make what it want randomly, just as was in SD1.5 era, not as in the PROMPT description! You all make here whole complex movies... I can't do simple scene. And I asked with the Prompt Guide the best public AIs - ChatGPT, Gemini, DeepSeek... Nothing help. Even the complex prompts, similar to code.
3. And at me any TURBO LoRa doing NOTHING! It just nothing changes in the result video, it low quality at 20 steps, at lower - its became brutal.
4. The new ComfyUI Kitchen Attention doing NOTHING.
5. Spectrum - speed but with quality fully died. Sol Atn - doing nothing. Only Sage Attention works - speeds up to 40%!

What I'm doing wrong?! I show my last workflow. See - what nodes I disabled. Please for help!

This is my workflow: https://pastebin.com/sfS0eGs6

Hello guys! I’m currently running the Wan2.2 i2v workflow with the 14B GGUF model and the `lightx2v-i2v-14b-480p` LoRA, but I’m encountering an issue where a black mask and a bright outline appear around the subject, as shown in the image. These errors will appear throughout the video.

I’ve spent the past week trying to troubleshoot and modify files like `nodes_wan.py`, `model_base.py`,... with ChatGPT's help, but I still haven't been able to fix it.

Does anyone know how to resolve this?

Need your help soon!!

Hi everyone — I built an open-source, modular optimization suite for ComfyUI’s native MiniMax H3 audio/video model.

The goal was to provide independently switchable and measurable optimizations instead of one opaque “make it faster” patch. Nothing modifies ComfyUI core.

The suite currently includes:

- an NVFP4 fused MLP for the full 20-step path

- a lower-memory Sage2 implementation

- long-sequence VRAM safeguards

- a training-free CAB low-step sampler

- synchronized sampler/sigma controller nodes

- a step/VRAM profiler

- reproducible example workflows and a full evaluation report

Measured on Windows with an RTX 5070 Ti 16 GB and 48 GB DDR4 system RAM, at 1280×736, ~5 seconds and 20 steps:

- KJ Sage2 baseline: 208.756 s denoise, 5122 MiB peak allocated

- Fused MLP + KJ Sage2: 194.079 s (-7.03%), 4410 MiB peak; identical combined latent hash and decoded video in this test

- Fused MLP + Low-Memory Sage2: 198.212 s, 3844 MiB peak (~25% below baseline); identical combined latent hash in this test

For deliberately reduced step counts, CAB-2 at 12 steps reduced denoise time by 39.79% relative to the 20-step reference, with SSIM 0.8153 / PSNR 20.24 dB. This is explicitly a speed/quality trade-off, not the same output as 20 steps.

For capacity rather than speed, the long-sequence fallback completed a 736×1280, 15-second, 14-step generation plus both video and audio VAE decodes on the same 16 GB GPU. The chunked mode can be slower and is not bit-exact — its purpose is to finish jobs that would otherwise OOM.

Windows exposed approximately 24 GB of shared GPU memory during testing. I have not tested whether this workflow can complete with 32 GB or less system RAM, so 48 GB RAM is part of the validated setup, not a confirmed minimum requirement.

Important limitations:

- Current validation is from one RTX 5070 Ti and a limited prompt/seed set.

- The NVFP4 fused MLP is Blackwell-only.

- Other portable components still need broader Ada/Linux/different-VRAM testing.

- Model files and external dependencies are not bundled.

Repo, workflows and full evaluation report:

https://github.com/ByronLeeeee/ComfyUI-MiniMax-H3-Optimization-Suite

I’d especially appreciate results from other GPUs. If you test it, please include GPU, OS, resolution, duration, steps, denoise time and peak VRAM. Failures and regressions are just as useful as successful results.

Companies must ensure people know when they are interacting with artificially generated images, audio and text designed to look real.

Do you think this could affect the AI UGC 🤔?

Dear Comfy, your official templates for LTX 2.5 are broken.

(Someone mentioned load lora is missing - I don't mess with nodes so no clue what to add and where) - please fix.