cuopt-server-api-python

Instructions for running NVIDIA cuOpt as a web server and sending it optimization problems through HTTP requests. cuOpt supports vehicle routing and linear or mixed-integer linear programming, but not quadratic programming through this interface.

In plain words
What is it for?
Use them to start cuOpt locally, in Docker, Kubernetes, or the cloud, then call it with Python, curl, or another HTTP client.
Why use it?
They explain how to choose a deployment method, prepare request fields, and diagnose rejected requests instead of guessing at the server or client setup.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/nvidia/skills/cuopt-server-api-python
Any agent
npx skills add NVIDIA/skills --skill cuopt-server-api-python
Clone the repo
git clone --depth 1 https://github.com/NVIDIA/skills

Made for: Claude Code, Codex.

Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,590 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00034 $0.01590
Opus 5 $0.00017 $0.00795
Sonnet 5 $0.00007 $0.00318
Haiku 4.5 $0.00003 $0.00159

Measured yesterday against content hash a663a623aa38, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

cuopt-server-api-python scanned grade A with 1 finding 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 yesterday.

The scan reads SKILL.md. This mod also ships 5 executable files (assets/lp_basic/client.py, assets/milp_basic/client.py, assets/pdp_basic/client.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

description: cuOpt REST server — start server, endpoints, Python/curl client examples. Use when the user is deploying or calling the REST API.
Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/cuopt-server-api-python/SKILL.md · 138 lines

How it starts

The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.

cuOpt Server — Deploy and client (Python/curl)

This skill covers starting the server and client examples (curl, Python). Server has no separate C API (clients can be any language).

Purpose

Use this skill when the user is deploying the cuOpt REST server or writing a client against it — choosing a deployment target, mapping a problem onto the HTTP endpoints, translating between Python-API and REST field names, or debugging a rejected payload.

Prerequisites

  • An NVIDIA GPU with a working CUDA driver (the server requires one; --gpus all for Docker).
  • cuopt-server installed, or Docker with the NVIDIA Container Toolkit. See the install skill.
  • Python clients need requests. No API key or auth token is required by the server itself.

Problem types supported

Problem type Supported
Routing
LP
MILP
QP

Required questions

Ask these if not already clear:

  1. Problem type — Routing or LP/MILP? (QP not available via REST.)
  2. Deployment — Local, Docker, Kubernetes, or cloud?
  3. Client — Which language or tool will call the API (e.g. Python, curl, another service)?

Start server

# Development
python -m cuopt_server.cuopt_service --ip 0.0.0.0 --port 8000

# Docker — pick the tag matching your CUDA major version
docker run --gpus all -d -p 8000:8000 -e CUOPT_SERVER_PORT=8000 \
  nvidia/cuopt:latest-cu13

Use latest-cu12 or latest-cu13 to match your driver's CUDA major version (latest-cu13-ubi10 for a UBI10 base). Prefer these over the CUDA+Python-specific tags such as latest-cuda12.9-py3.13 — those track a single Python line and go stale when it stops receiving builds.

For production, pin rather than float: latest-* tags are mutable and can silently move to a different image. Use a full release tag (nvidia/cuopt:<release>-cuda<cuda>-py<python>) or an immutable digest (nvidia/cuopt@sha256:<digest>). Check the nvidia/cuopt registry for available tags.

Read the full file on GitHub · 138 lines

Changes

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.

  1. yesterday First seen · 138 lines · 34 tokens per session scan A a663a623aa38

Subscribe to this mod's changes

cuopt-server-api-python is a skill published in the GitHub repository NVIDIA/skills (3,144 stars, last pushed 2d ago), licensed Apache-2.0. It adds 34 tokens to every session and 1,590 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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