Liquid Compute GPU test MCP server

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. 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 LTS or later with NVIDIA drivers;
• 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

Shortened. The full README is on GitHub.