Paralon 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

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

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

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 Max rentals running at once as a safety cap.
3. 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 PARALON_API_KEY env var — you never edit the server.

Claude Desktop — claude_desktop_config.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: PARALON_BASE_URL (defaults to https://paraloncloud.com/api/v1).

3. Try it

"List the cheapest GPUs I can rent, then start a 2-hour Jupyter rental on one with at least 24GB of VRAM."

The agent calls list_gpus, picks a node, and calls create_rental with hours: 2. It then polls get_rental for the Jupyter URL. Say "stop it" and it calls destroy_rental.

As a provider:

"How are my nodes doing? Is any GPU running hot?"

"Take rig-2 off the market for the afternoon, and set rig-1 to $0.60 an hour."

"How much did I earn this week, and from which node?"

Safety

• create_rental and destroy_rental change what you're billed — your MCP client will ask you to approve them (Claude Code/Desktop confirm tool calls by default). Keep that on.
• create_rental auto-generates an idempotency key, so a retried call never starts a second GPU.
• Pass hours so a rental auto-stops even if the agent forgets to.
• The key's max_active_rentals limit (set in the Console) caps concurrency regardless.
• The node tools that change something (add_node, set_node_available, set_node_price, update_node, reclaim_spot_node, set_node_access) tell the agent to confirm with you first; reclaim_spot_node stops a renter's spot rental two minutes later.
• add_node and get_node_install_command return a command with the node's secret token: keep it private.
• Give the agent a key with only the scopes it needs.

Test

npm install
PARALON_API_KEY=prlc_your_key_here node smoke-test.mjs

It calls the read-only tools, and the node tools only on a node that does not exist, so it changes nothing.

Run locally (dev)

PARALON_API_KEY=prlc_your_key_here node server.js

Links

• Rental API docs: https://paraloncloud.com/docs/rental-api
• Provider API docs: https://paraloncloud.com/docs/provider-api
• Console (create keys): https://paraloncloud.com/console
• Inference API: https://paraloncloud.com/docs/inference-api

MIT