ParalonCloud MCP server

ParalonCloud MCP server

Rent GPUs from inside your AI agent, and, if you provide GPUs, run your own nodes from it. This is an MCP server for the ParalonCloud Rental API and Provider API: it lets Claude Code, Claude Desktop, Cursor, or any MCP client

install command, take a node off the market and back, set its price, reclaim a spot node, and read your earnings,

• rent: browse GPUs, start a rental, get its connection URL, and stop it;
• provide: list your nodes with live GPU load and temperature, add a node and get its

using natural language.

One key for everything: the same prlc_ key powers ParalonCloud's

OpenAI-compatible inference API. Build an

agent that calls a model and rents the GPU to run the heavy job.

Formerly @paraloncloud/mcp-rentals. That package is deprecated: switch your config to @paraloncloud/mcp.

Tools

Renting (key needs the rental scope)

Your nodes, for GPU providers (key needs the nodes scope)

Payouts are not reachable from the API or this server. Deleting a node stays on the site.

Setup

1. Get a key with the right scope

Max rentals running at once as a safety cap.

1. Create an API key in the Console.
2. To rent, turn on GPU rentals for that key (rentals are opt-in), and optionally set

1. To manage your own nodes, turn on My nodes. One key can have both.

Use a dedicated key for the agent, not your production key.

2. Add it to your MCP client

The client passes your key via the PARALONAPIKEY env var — you never edit the server.

Claude Desktop — claudedesktopconfig.json:

{
  "mcpServers": {
    "paraloncloud": {
      "command": "npx",
      "args": ["-y", "@paraloncloud/mcp"],
      "env": {
        "PARALON_API_KEY": "prlc_your_key_here"
      }
    }
  }
}

Claude Code — one command:

claude mcp add paraloncloud \
  --env PARALON_API_KEY=prlc_your_key_here \
  -- npx -y @paraloncloud/mcp

Cursor — .cursor/mcp.json (same shape as Claude Desktop above).

Optional env: PARALONBASEURL (defaults to https://paraloncloud.com/api/v1).

3. Try it

Shortened. The full README is on GitHub.