Paraloncloud Rentals
БесплатноНе проверенEnables MCP clients to rent GPUs from ParalonCloud using natural language, including browsing available GPUs, starting and stopping rentals, and retrieving conn
Описание
Enables MCP clients to rent GPUs from ParalonCloud using natural language, including browsing available GPUs, starting and stopping rentals, and retrieving connection URLs.
README
Rent GPUs from inside your AI agent. This is an MCP server for the ParalonCloud Rental API: it lets Claude Code, Claude Desktop, Cursor, or any MCP client browse GPUs, start a rental, get its connection URL, and stop it — 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.
Tools
| Tool | What it does | Cost |
|---|---|---|
list_gpus |
List rentable GPUs with price, VRAM, compute capability, country | free |
get_balance |
Your credit balance | free |
create_rental |
Start a Jupyter rental (async → poll) | spends credits |
get_rental |
Status + connection URL once running | free |
list_rentals |
Your active rentals (status: "all" for history) |
free |
destroy_rental |
Stop a rental and stop billing | — |
Setup
1. Get a key with the rental scope
- Create an API key in the Console.
- Turn on the GPU Rentals scope for that key (rentals are opt-in).
- Optionally set Max rentals running at once as a safety cap.
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-rentals": {
"command": "npx",
"args": ["-y", "@paraloncloud/mcp-rentals"],
"env": {
"PARALON_API_KEY": "prlc_your_key_here"
}
}
}
}
Claude Code — one command:
claude mcp add paraloncloud-rentals \
--env PARALON_API_KEY=prlc_your_key_here \
-- npx -y @paraloncloud/mcp-rentals
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.
Safety
create_rentalanddestroy_rentalchange 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_rentalauto-generates an idempotency key, so a retried call never starts a second GPU.- Pass
hoursso a rental auto-stops even if the agent forgets to. - The key's
max_active_rentalslimit (set in the Console) caps concurrency regardless.
Run locally (dev)
PARALON_API_KEY=prlc_your_key_here node server.js
Links
- Rental API docs: https://paraloncloud.com/docs/rental-api
- Console (create keys): https://paraloncloud.com/console
- Inference API: https://paraloncloud.com/docs/inference-api
MIT
Установка Paraloncloud Rentals
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/ParalonCloud/mcp-rentalsFAQ
Paraloncloud Rentals MCP бесплатный?
Да, Paraloncloud Rentals MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Paraloncloud Rentals?
Нет, Paraloncloud Rentals работает без API-ключей и переменных окружения.
Paraloncloud Rentals — hosted или self-hosted?
Доступен hosted-вариант: Unyly запускает сервер в облаке, локальная установка не обязательна.
Как установить Paraloncloud Rentals в Claude Desktop, Claude Code или Cursor?
Открой Paraloncloud Rentals на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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