Runcrate MCP

Give your AI agent GPUs. Runcrate is the AI cloud for developers and agents: connect it once, then ask in plain words. Your agent sees live GPU prices, launches a GPU on a ready image, runs your command as a job whose machine stops (and stops billing) when the command exits, schedules runs, moves files, and checks your spend.

• Server: https://mcp.runcrate.ai/mcp (streamable HTTP)

• Sign-in: OAuth in your browser. No key to copy, nothing to paste into a config file.

• Tools for instances, clusters, jobs, schedules, files, volumes, firewall and HTTPS links, billing, environments and secret names. Tool reference

You pick one environment when you sign in. The agent acts only there, and that environment's monthly budget caps what it can spend.

Connect your agent

Paste this one line into your agent: Claude Code, Codex, Cursor, VS Code, OpenCode, or any agent that can run a command. It adds the server to itself, and its first Runcrate tool call opens your browser to sign in.

Add Runcrate's MCP server to yourself: run curl -fsSL "https://runcrate.ai/mcp.md" and follow it.

Or one click:

In Claude Code, the plugin adds the server and a skill that teaches Claude how to spend safely: /plugin marketplace add runcrateai/runcrate-mcp, then /plugin install runcrate@runcrate. In Gemini CLI: gemini extensions install https://github.com/runcrateai/runcrate-mcp.

The same skill installs into Codex, Cursor, Gemini CLI and other agents that read Agent Skills: npx skills add runcrateai/runcrate-mcp --skill runcrate. It teaches your agent to check live prices (https://www.runcrate.ai/pricing.md), run work with a max runtime, stop what it started, and top up when the balance runs low.

Claude and ChatGPT on the web can't run a command, so they take the URL as a custom connector (steps below).

With the Runcrate CLI, one command connects every client it finds on your machine:

runcrate mcp install

Claude Code

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

Then run /mcp in Claude Code and pick runcrate: your browser opens to sign in.

Claude (claude.ai and Claude Desktop)

1. Open Settings > Connectors and choose Add custom connector.

2. Name it Runcrate and paste https://mcp.runcrate.ai/mcp.

3. Choose Connect and sign in to Runcrate in the window that opens.

ChatGPT

1. Open chatgpt.com/plugins, choose +, then Add custom MCP server.

2. Name it Runcrate and paste https://mcp.runcrate.ai/mcp as the URL, with OAuth.

3. Create it, sign in to Runcrate, then mention @Runcrate in a chat.

Codex

codex mcp add runcrate --url https://mcp.runcrate.ai/mcp

Codex opens your browser to sign in. Closed it? Run codex mcp login runcrate.

Windsurf and Devin

Run runcrate mcp install --client windsurf, or add a server in Cascade's MCP settings with the URL https://mcp.runcrate.ai/mcp. Devin CLI: devin mcp add -s user runcrate https://mcp.runcrate.ai/mcp, then devin mcp login runcrate.

Zed, Warp, Goose, Raycast and any other MCP client

Give the client the URL https://mcp.runcrate.ai/mcp and choose OAuth (dynamic registration). It signs you in through your browser on first use.

Config files

Cursor (~/.cursor/mcp.json), Warp (~/.warp/.mcp.json) and most clients:

{ "mcpServers": { "runcrate": { "url": "https://mcp.runcrate.ai/mcp" } } }

VS Code (mcp.json in your user profile):

{ "servers": { "runcrate": { "type": "http", "url": "https://mcp.runcrate.ai/mcp" } } }

Windsurf (mcp_config.json): { "mcpServers": { "runcrate": { "serverUrl": "https://mcp.runcrate.ai/mcp" } } }

Zed (settings.json): "context_servers": { "runcrate": { "url": "https://mcp.runcrate.ai/mcp" } }

Gemini CLI (~/.gemini/settings.json): { "mcpServers": { "runcrate": { "httpUrl": "https://mcp.runcrate.ai/mcp" } } }

Codex (~/.codex/config.toml):

[mcp_servers.runcrate]
url = "https://mcp.runcrate.ai/mcp"

Goose (~/.config/goose/config.yaml):

extensions:
  runcrate:
    name: Runcrate
    type: streamable_http
    uri: https://mcp.runcrate.ai/mcp
    enabled: true

Related MCP server: Massed Compute MCP Server

Try it

Launch an H100 with the Finetune crate and run nvidia-smi.

Run python train.py on an A100 as a job, at most 2 hours, and follow the logs.

How much of this month's budget is left?

What is in this repo

The server itself is hosted by Runcrate; this repo only packages the connection. It is listed in the official MCP registry as io.github.aeonmindai/runcrate.

Links

• Docs: https://runcrate.ai/docs/mcp/setup

• Product: https://runcrate.ai/mcp

• CLI: https://github.com/runcrateai/runcrate-cli

• Support: support@runcrate.ai

• Privacy: https://www.runcrate.ai/privacy

• Terms: https://www.runcrate.ai/terms

MIT licensed.