Liquid Compute GPU test

Name: Liquid Compute GPU test
Author: Liquid-Compute

by Liquid-Computeversion 1.0.1i★ –iRuns in the cloud

Registry namecom.liquidcompute/gcat

Install

Overview

Description from the maker (original English)

Run GPU acceptance tests on your NVIDIA GPU nodes over SSH: DCGM, GEMM, HBM/PCIe bandwidth, NCCL.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs in the cloud
Transport: Streamable HTTP
Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on the maker’s server: what you ask it goes through their server.
The registry lists no key to fill in.

You need

Runs in the cloudNothing to install; it connects over the internet

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Works in Claude on the web, desktop and mobile:

Open Settings → Connectors
Press Add custom connector
Paste the address below and press Add
If it asks you to sign in, sign in with the maker

https://api.liquidcompute.co/mcp

Run this in your terminal

claude mcp add --transport http gcat https://api.liquidcompute.co/mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "gcat": {
      "url": "https://api.liquidcompute.co/mcp"
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "gcat": {
      "type": "http",
      "url": "https://api.liquidcompute.co/mcp"
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

ChatGPT connects only to servers on the internet:

Open ChatGPT on the web → Settings → Connectors (Apps)
Press Create or Add (some plans need Developer mode under Advanced first)
Paste the address below, give it a name and save
If it asks you to sign in, sign in with the maker

https://api.liquidcompute.co/mcp

Menu names can differ slightly by plan and over time.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

We have not read this server’s tool list yet; we check endpoints in rotation.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified against the domain liquidcompute.com (the registry checks domain ownership)
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
… Not checked yet
Endpoint responds
Not checked yet; we check endpoints in rotation
… Not checked yet
Sign-in with OAuth
Not checked yet; we check endpoints in rotation
… Not checked yet
No hidden instructions in tool descriptions
Not checked yet; we read the tool list when we check the endpoint

Compared with others in Otheri

More stars than 0% of the other 32489 servers in this category
Published to the registry more recently than 64% of the other 32489 servers in this category
Basic checks equal to or better than 100% of the other 32489 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Liquid Compute GPU test safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.1) reached the registry 22 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Whisper

Alternatives

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Whisper

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One routable IPv6 per AI agent, verifiable from the DNS root. Keyless tools need no signup.

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Liquid Compute GPU test (GCAT)

Run GPU acceptance tests on NVIDIA GPU nodes you administer, from your AI agent.

Liquid Compute connects to your nodes over SSH from its own servers. It runs NVIDIA DCGM diagnostics, a CUTLASS GEMM benchmark, HBM and PCIe bandwidth tests and NCCL all-reduce for a GPU profile, then reports every measurement against that profile's thresholds. Profiles cover A10 nodes, H100 and H200 8-GPU nodes and 2- or 4-node clusters over RDMA, and B200 and B300 8-GPU nodes. Your agent can list the current ones.

The test is free and needs a Liquid Compute account. New to Liquid Compute? Create your account and finish setup on the website first. Your agent asks you to sign in the first time it connects.

This repository holds no code. The hosted MCP server at https://api.liquidcompute.co/mcp does the work; this repository has the listing files for agent marketplaces and an agent skill that teaches agents the test flow.

Requirements

Every node needs:

Ubuntu 22.04 or 24.04 with NVIDIA driver 580 or later (CUDA 13.0 or later);
a public IP address that accepts SSH from the source addresses Liquid Compute gives you when you create a test;
a user with root or passwordless sudo;
idle GPUs for the whole test. A test puts every GPU under full load for the profile's duration, which can be 90 minutes or longer.

Connect your agent

The server uses Streamable HTTP and OAuth 2.1 sign-in with the gpu_tests scope.

Claude Code

Install the plugin, which adds the server and the skill:

claude plugin marketplace add Liquid-Compute/gcat

claude plugin install liquidcompute-gcat@liquidcompute

Or add only the server:

claude mcp add --transport http --scope user liquidcompute-gpu-test https://api.liquidcompute.co/mcp

Then run /mcp in Claude Code to sign in.

Claude apps

In Claude, open Customize > Connectors, select Add custom connector and enter https://api.liquidcompute.co/mcp. On Team and Enterprise plans, an Owner adds it under Organization settings > Connectors.

Codex

codex mcp add liquidcompute-gpu-test --url https://api.liquidcompute.co/mcp

codex mcp login liquidcompute-gpu-test

ChatGPT

Open chatgpt.com/plugins, select +, then Add custom MCP server. Enter https://api.liquidcompute.co/mcp and choose OAuth. Your workspace settings decide whether custom MCP servers are allowed.

Cursor

Open this install link in your browser:

cursor://anysphere.cursor-deeplink/mcp/install?name=liquidcompute-gpu-test&config=eyJ1cmwiOiJodHRwczovL2FwaS5saXF1aWRjb21wdXRlLmNvL21jcCJ9

Or add the server to ~/.cursor/mcp.json:

"mcpServers": { "liquidcompute-gpu-test": { "url": "https://api.liquidcompute.co/mcp" } } }

VS Code

Run MCP: Add Server, choose HTTP and enter https://api.liquidcompute.co/mcp. Or add it to .mcp.json at your workspace root:

"mcpServers": { "liquidcompute-gpu-test": { "type": "http", "url": "https://api.liquidcompute.co/mcp" } } }

Gemini CLI

Install the extension, which adds the server and the skill:

gemini extensions install https://github.com/Liquid-Compute/gcat

Or add only the server, then sign in with /mcp auth liquidcompute-gpu-test:

gemini mcp add --transport http --scope user liquidcompute-gpu-test https://api.liquidcompute.co/mcp

How a test runs

Your agent picks the profile that matches your nodes and creates a test. You get one authorized_keys line and the addresses Liquid Compute connects from.
You add the line for a root or passwordless-sudo user on every node, or let your agent add it over SSH access you gave it.
You confirm that you are authorized to give Liquid Compute SSH access. Your agent adds the nodes, and Liquid Compute runs a brief connection check that does not load the GPUs.
You confirm that the nodes are reserved, their GPUs will stay idle, and you are authorized to run the test. The test starts.
Your agent follows the test and reads you the report. It can also create a link to the report that anyone with the link can open for 30 days.
You remove the authorized_keys line.

The skill has the full flow and the tools it uses.

A report measures your nodes during the test window. It is not a certification or a warranty. If your GPUs pass and you own them, you can list them for rent on Liquid Compute.

Safety

Two confirmations only you can give. The server refuses to add nodes or start a test until your agent passes your own confirmation (steps 3 and 4). The skill tells agents to show you the exact wording and never to confirm for you. Don't set your client to auto-approve these two tools.
Annotated tools. Every tool says whether it only reads, and starting and stopping a test are marked destructive, so your client can ask before running them.
Nothing installed. Test files are copied to the nodes for the test and removed afterwards. Liquid Compute installs no packages, services or accounts and changes no settings.
Access you control. Liquid Compute can reach a node over SSH until you remove its authorized_keys line.

Data

Sign-in uses your Liquid Compute account. The token your agent receives is issued for this server only.
Liquid Compute stores the tests you create, the node addresses and user names you add, the hardware details and raw output the test collects, connection-check results and test reports, under your company's account, until you ask for them to be deleted.
Reports stay available until the expiry shown when you create a test. Share links last 30 days.

Liquid Compute's Terms of Service and GPU test privacy notice apply. The notice lists what a test collects, how Liquid Compute uses it, how long it is kept and how to ask for it to be deleted.

Support

Open an issue at github.com/Liquid-Compute/gcat/issues for help with the server, the skill or a test. Issues are public, so don't post node addresses, keys or report links in them. Send privacy requests to privacy@liquidcompute.com.

License

The listing files and skill text in this repository are under the MIT License. Use of the Liquid Compute service is governed by its Terms of Service.

Liquid Compute GPU test

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Whisper

README from the maker

Liquid Compute GPU test (GCAT)

Requirements

Connect your agent

Claude Code

Claude apps

Codex

ChatGPT

Cursor

VS Code

Gemini CLI

How a test runs

Safety

Data

Support

License