Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/blockrunai/blockrun-mcp/modalnpx skills add BlockRunAI/blockrun-mcp --skill modalgit clone --depth 1 https://github.com/BlockRunAI/blockrun-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/blockrunai/blockrun-mcp/modal)<a href="https://agentmods.dev/skills/blockrunai/blockrun-mcp/modal"><img src="https://agentmods.dev/badge/skills/blockrunai/blockrun-mcp/modal.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00062 | $0.02303 |
| Opus 5 | $0.00031 | $0.01151 |
| Sonnet 5 | $0.00012 | $0.00461 |
| Haiku 4.5 | $0.00006 | $0.00230 |
Grade A, and why
modal scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Modal Sandboxes
Disposable remote containers (with optional GPU) via Modal, paid per call in USDC. No Modal account, no GPU procurement.
Base only. sol.blockrun.ai carries the /v1/modal/* routes but has no Modal backend
configured, so every action — create, exec, status, terminate — answers 503. That reads
as "the sandbox service is down" rather than "wrong chain", which is exactly the wrong
conclusion to act on: retrying will not help. The tool checks the active chain first and
says so. Switch with blockrun_wallet action:"chain" chain:"base". Prices below are Base
prices and include its per-transaction fee.
READ THIS BEFORE SETTING timeout
timeout is the BILLED lifetime, charged upfront in full, and never refunded — not an idle timeout. Above 300s the price switches from a flat rate to per-hour billing for the entire duration you ask for, whether you use it or not. Terminating early refunds nothing.
That makes timeout the single most expensive field in this MCP:
| what you ask for | what you pay |
|---|---|
{ timeout: 300 } |
$0.0110 |
{ timeout: 300, gpu: "A100" } |
$0.2010 |
{ timeout: 600, gpu: "A100" } |
$0.6677 |
{ timeout: 86400, gpu: "H100" } |
$192.0010 |
All four are live-verified quotes. A 24h H100 sandbox costs $192 upfront, non-refundable, even if your job finishes in a minute.
So: ask for the time you need, not a safe-looking ceiling. Need 20 minutes of H100? timeout: 1200 is $2.67, not $192. Keep timeout ≤ 300 and you stay on the flat rate entirely.
How to Call from MCP
// 1. Create — timeout: 300 keeps you on the FLAT rate ($0.0110, or $0.2010 with A100).
// Anything above 300 bills hourly for the full requested lifetime, no refund.
blockrun_modal({ path: "sandbox/create", body: {
image: "python:3.11",
gpu: "A100",
timeout: 300,
setup_commands: ["pip install torch transformers"]
}})
// returns { sandbox_id, ... }
// 2. Exec
blockrun_modal({ path: "sandbox/exec", body: {
sandbox_id: "sb_abc...",
command: ["python", "-c", "import torch; print(torch.cuda.get_device_name(0))"]
}})
// 3. Terminate
blockrun_modal({ path: "sandbox/terminate", body: { sandbox_id: "sb_abc..." } })
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 174 lines · 62 tokens per session scan A 6f0eaa3881a8
modal is a skill published in the GitHub repository BlockRunAI/blockrun-mcp (393 stars, last pushed yesterday), licensed MIT. It adds 62 tokens to every session and 2,303 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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