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computenexa-gpuInfrastructure

ComputeNexa MCP Server

Official

Launch a machine

launch_machine

Request a cost quote, then launch a GPU machine after approval; booked hours are charged upfront and unused time is refunded.

Instructions

Launch a GPU machine. Costs money: call first with confirm=false to get a quote (nothing happens), show it to the person, and only after they agree call again with the same arguments, confirm=true and expected_total_usd. The booked time is charged up front from the team's balance.

Input Schema

NameRequiredDescriptionDefault
appYesApp from list_apps, e.g. datascience
gpuYesGPU slug from list_gpus, e.g. rtx-a6000
hoursYesHow long to book; unused time is refunded
labelNoA name for the machine
modelNoFor apps with models; left out = our recommendation for this GPU
regionNoWhere it must runany
confirmNofalse = only quote (default); true = launch, after the person agreed to the quote
projectNoProject name or id to restore into ~/work and save back
endpointNoEndpoint name or id this machine serves
gpu_countNo
expected_total_usdNoWith confirm=true: the quote's total_usd the person agreed to
keep_running_hoursNoRenew this many hours at a time until stopped

Output Schema

NameRequiredDescriptionDefault
quoteNo
statusYesquote = nothing happened yet; done = it was carried out
machineNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond annotations, the description discloses the critical financial behavior: the launch costs money, confirm=false produces only a quote and does nothing, and booked time is charged up front from the team balance. This is exactly the kind of consequence-focused context an agent needs for a non-read-only, open-world mutation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with purpose and cost warning, then gives the required confirmation workflow without unnecessary detail. Every sentence serves selection or safe invocation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 12-parameter financial mutation with high schema coverage and an output schema, the description covers the essential missing context: cost, quote mode, confirmation requirement, and upfront charging. Return-value details are appropriately left to the output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is high at 92%, so the schema already carries most parameter meaning. The description nevertheless adds useful procedural semantics for confirm and expected_total_usd by explaining the two-call quote-then-confirm workflow and the need to reuse the same arguments.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Launch a GPU machine.' It also immediately frames the operation as a paid action, which makes the tool's core purpose unmistakable against siblings like list_gpus, stop_machine, and extend_machine.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit invocation guidance: call first with confirm=false to get a no-op quote, show it to the person, then call again with confirm=true and expected_total_usd after agreement. It does not explicitly mention alternatives such as extend_machine for renewing an existing machine, so it falls short of full when-to-use-vs-alternative guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.