modal

Create, execute, and terminate remote Modal sandboxes with optional GPU access.

473|52|Updated Jan 12, 2026
One-click install
npx skills add https://github.com/BlockRunAI/blockrun-mcp --skill modal-blockrunai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: modal
Source: https://github.com/BlockRunAI/blockrun-mcp/tree/main/skills/modal
Command: npx skills add https://github.com/BlockRunAI/blockrun-mcp --skill modal-blockrunai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Disposable remote containers (with optional GPU) via Modal, paid per call in USDC. No Modal account, no GPU procurement — pay only for what runs.

Core Features & Use Cases

  • On-demand sandboxed execution with optional GPU access to run isolated tasks.
  • Create, execute, monitor status, and terminate sandboxes without local hardware.
  • Suitable for testing untrusted code, GPU-accelerated experiments, or heavy compute in a disposable environment.

Quick Start

Create a disposable sandbox with a Python image, run a command, and terminate when done.

Frequently Asked Questions about modal

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run isolated code execution for untrusted scripts remotely?▼

You can run isolated code execution by provisioning disposable Modal sandboxes, which securely handle untrusted scripts without risking your local environment.

Can I run GPU-accelerated tasks without provisioning local hardware?▼

GPU-accelerated tasks can run without local hardware by selecting GPU options when creating a remote Modal sandbox, billed per call in USDC.

What is the best way to execute heavy compute jobs in a disposable environment?▼

Heavy compute jobs in a disposable environment are best executed via remote Modal sandboxes, which provide cost-aware orchestration through create, exec, and terminate endpoints.

Do I need a Modal account to run sandboxed remote execution?▼

A Modal account is not required for sandboxed remote execution; the service provisions sandboxes directly and charges you only for what runs in USDC.

How do I create and terminate a Python sandbox for ad-hoc runs?▼

Creating and terminating a Python sandbox for ad-hoc runs involves using sandbox endpoints to provision a Python image, execute commands, and terminate the sandbox when finished.

Are there limitations to running heavy compute tasks in remote sandboxes?▼

Limitations of running heavy compute in remote sandboxes include being restricted to available GPU selections and incurring variable costs based on execution duration and compute intensity.