How to give Claude Code, Codex or Cursor access to GPUs (MCP setup)

Oct 8, 2026 - 3 min read

Short answer: connect your coding agent to a GPU platform’s MCP server. The agent can then estimate, launch, watch and fetch results from GPU jobs from the same chat where it wrote the code. With Nodus the connection stays in your coding tool. Review the Job manifest and estimate before authorizing its creation.

Coding agents are great at writing a training script and terrible at the part after: finding a GPU, shipping code to it, watching logs, copying results back. MCP closes that loop.

Claude Code

claude mcp add --scope user --transport http nodus https://mcp.nodus-compute.ai/mcp

Then run /mcp, pick nodus, and sign in in your browser. Reuse an existing working connection. The connect page has current setup instructions.

Codex

codex mcp add nodus --url https://mcp.nodus-compute.ai/mcp
codex mcp login nodus

Cursor

Add this to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "nodus": { "type": "http", "url": "https://mcp.nodus-compute.ai/mcp" }
  }
}

Any other MCP client

Add a remote HTTP MCP server with URL https://mcp.nodus-compute.ai/mcp and follow the sign-in prompt. Prefer a local server? Install the CLI and run nodus mcp install, which configures the agents on your machine.

Activate your account

Creating a new organization requires a verified email and a verified card. Complete that setup in your browser; card verification does not charge the card or enable auto-recharge. Eligible accounts receive a $30 starter grant valid for 30 days. An invited teammate uses the organization’s existing billing. Check your available balance before running compute.

Verify without spending money

Ask the agent: “List my Nodus jobs.” That is read only. A good first prompt for any agent that can read URLs:

Read https://nodus-compute.ai/connect.md and help me connect Nodus to this agent.
Verify setup by listing my jobs. Do not start paid compute.

Get your first result

Use the small training example: it includes the complete script, a $1 spending limit, a 10-minute timeout, a dry-run command, and a declared metrics.json output. Those limits are example choices, not a price or completion guarantee.

Read https://www.nodus-compute.ai/docs/source/getting-started/quickstart.md.
Prepare that example for my Nodus project. Show the image, source, command,
limits, output declaration, and current estimate. Wait for my approval before
submitting paid compute. After approval, follow the run to its terminal status
and retrieve metrics.json if it succeeds. Do not report success from submission alone.

The hosted server cannot read your laptop’s files. Use an image containing your code, or upload it through the CLI workflow. The local MCP server additionally supports source upload and verified output downloads. The MCP guide explains both paths.

What the agent can actually do

The server exposes generic tools over every resource: get, describe, logs, estimate, apply, exec and more. In practice that means prompts like:

“Run train.py on a 24 GB GPU with a $5 cap and stream the logs.”
“Why did job/train fail?”
“Fine-tune Qwen3 0.6B with LoRA on chats.jsonl and download the adapter.”
“What did my sandboxes cost this week?”

Guardrails that matter when an agent holds your credit card

Review resource creation. apply returns a dry run; creation requires confirmed: true and its accepted etag. Other write tools do not use this handshake. Keep client approvals enabled for actions such as deletion or command execution.
Same limits as you. The agent uses your account, projects, budgets and spending caps. A project budget stops it from overspending even if it gets creative.
Set Job limits. Choose maxCostUSD and a timeout before launch. Saved training progress requires your program to write and load checkpoint files; a spending limit alone does not save model state.
Frozen rates. The hourly rate is fixed when the machine is chosen and holds for the whole run.

FAQ

Do I need a separate “agents” product to use Claude Code with GPUs? No. MCP is enough. Managed Agents (Beta) is a different feature for running agents inside Nodus.

Which GPU does the agent get? By default the cheapest offering that fits the request and can start now, within your limits. You can ask for a specific type like H100 or B200.

What does it cost to try? Eligible activated accounts receive a $30 starter grant. Email and card verification are required; check your balance and estimate before submitting paid work.

Setup for every client: nodus-compute.ai/connect