CUDO Compute API

✓ Official Vendor SpecCloud InfrastructureComputebearer122 EndpointsREST

For Agents

Provision and manage GPU and CPU virtual machines, disks, networks, and object storage on the CUDO Compute cloud. Useful for AI agents that orchestrate ephemeral training, inference, or batch jobs on green compute.

Quickstart

Get started with CUDO Compute API in minutes using your preferred integration method.

# Add to your MCP client config (Claude Desktop, Cursor, Windsurf)
{
  "jentic": {
    "url": "https://api.jentic.com/mcp",
    "auth": "oauth"
  }
}

# Then ask your agent:
"provision a GPU virtual machine on CUDO Compute"

# → Jentic returns the GET /events tool with parameter schema, agent executes.

Capabilities

What an agent can do with CUDO Compute API API.

Provision GPU or CPU virtual machines and start, stop, or terminate them via the /v1/projects/{projectId}/vms operations

Attach, detach, and resize block storage disks for VM workloads

Manage virtual networks and security groups for isolated agent fleets

Create and manage object storage buckets and credentials for model artefacts

GET STARTED

Start building with CUDO Compute API API

Explore with Jentic

View OpenAPI Document

The CUDO Compute API is a REST interface to the CUDO Compute cloud, a sustainable GPU and CPU cloud provider. The API covers the full lifecycle of cloud resources: virtual machines, disks, images, networks, object storage, and clusters, plus the supporting plane of projects, billing accounts, and API keys. Resource-oriented URLs use predictable path patterns, JSON request and response bodies, and standard HTTP verbs and status codes. Authentication is via a bearer token sent in the Authorization header.

Use Cases

Patterns agents use CUDO Compute API API for, with concrete tasks.

★ On-Demand GPU Provisioning for Training Jobs

An ML training agent can request a GPU virtual machine, run a job, store the resulting checkpoint to CUDO object storage, and terminate the VM, all through the API. Billing-account spend endpoints let the agent abort if the project is over budget. Useful when training jobs are bursty and the team does not want to keep an expensive GPU running between runs.

Call POST /v1/projects/{projectId}/vms with a GPU machine type, run the training script, then DELETE the VM when the run completes.

Multi-Tenant Inference Fleet

A platform that serves AI inference can manage a fleet of CUDO VMs scaled by demand. Use the network and security-group endpoints to isolate tenants, attach object storage for model weights, and rotate API keys per tenant. CUDO's spend reporting lets the platform price inference accurately per customer.

Provision N GPU VMs in a project network, attach the model checkpoint disk, and register them behind the inference router.

Cost-Aware Batch Compute

A research team running nightly batch jobs can have an agent watch the billing-account spend endpoints and decide how many CUDO VMs to launch within the day's budget. Combine /v1/billing-accounts/{billingAccountId}/spend/details with the VM lifecycle endpoints to keep nightly batch runs within a fixed monthly cost.

Call GET /v1/billing-accounts/{billingAccountId}/spend/details, then provision additional VMs only if remaining budget exceeds the cost of one machine-hour.

AI Agent Integration via Jentic

An infrastructure agent can use Jentic to discover the CUDO Compute operations it needs without reading 122 endpoint definitions. Jentic stores the bearer token and exposes operations like 'create a GPU VM' and 'list virtual machines' as semantic tools so the agent picks the right call from natural-language intent.

Use Jentic search for 'provision a GPU virtual machine', load the CUDO Compute /v1/projects/{projectId}/vms create schema, and execute it for the project.

Key Endpoints

122 endpoints — the cudo compute api is a rest interface to the cudo compute cloud, a sustainable gpu and cpu cloud provider.

METHOD

PATH

DESCRIPTION

GET

/v1/api-keys

List API keys

POST

/v1/api-keys

Create an API key

GET

/v1/billing-accounts

List billing accounts

GET

/v1/billing-accounts/{billingAccountId}/spend/details

Get billing account spend details

POST

/v1/billing-accounts/{id}:add-permission

Add a billing account permission

GET

/v1/api-keys

List API keys

POST

/v1/api-keys

Create an API key

GET

/v1/billing-accounts

List billing accounts

GET

/v1/billing-accounts/{billingAccountId}/spend/details

Get billing account spend details

POST

/v1/billing-accounts/{id}:add-permission

Add a billing account permission

Why though Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

The CUDO Compute bearer token is stored encrypted in the Jentic MAXsystem vault and injected into the Authorization header at request time. Agents see scoped tool access, never the raw token.

Intent-based discovery

Agents search Jentic by intent (for example 'provision a GPU virtual machine') and Jentic returns the matching CUDO Compute operation with its input schema, so the agent does not have to hunt through 122 endpoints.

Time to first call

Direct integration is roughly a week to model VMs, disks, networks, billing, and credentials. Through Jentic the integration is under an hour because each operation is exposed as a discoverable tool with its schema.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Alternative

DigitalOcean API

DigitalOcean is an alternative cloud for general-purpose VMs and managed services.

Choose DigitalOcean when the workload is general-purpose CPU and managed databases; choose CUDO Compute when the priority is GPU access and sustainable energy.

Alternative

Linode API

Linode (Akamai) provides similar cloud compute primitives at a different price and region mix.

Use Linode for global CPU compute with Akamai's network; use CUDO Compute when you specifically want GPU instances on a green cloud.

Alternative

Paperspace API

Paperspace specialises in GPU notebooks and ML workflows, overlapping with CUDO's GPU VMs.

Choose Paperspace for managed ML notebooks and Gradient pipelines; choose CUDO Compute for raw GPU VM provisioning with full network control.

Alternative

Hetzner Cloud API

Hetzner Cloud is a low-cost alternative for CPU VMs and storage.

Use Hetzner for inexpensive CPU VMs in Europe; use CUDO Compute when GPUs and global GPU regions are required.

FAQs

Specific to using CUDO Compute API API through Jentic.

What authentication does the CUDO Compute API use?

CUDO Compute uses a bearer token in the Authorization header. You generate the key in the CUDO Compute console under API keys. Through Jentic the token is held in the encrypted MAXsystem vault and never enters the agent's prompt or model output.

Can I provision a GPU virtual machine with the CUDO Compute API?

Yes. POST /v1/projects/{projectId}/vms with a body that selects a GPU machine type, an image, and a region creates a new VM. You can pair this with the disks, networks, and object-storage operations to set up a full training environment.

What are the rate limits for the CUDO Compute API?

The OpenAPI spec does not publish specific rate limits, but CUDO applies sensible per-account throttling on control-plane operations. Batch large fleet provisioning steps and back off on 429 responses.

How do I list my running VMs with the CUDO Compute API through Jentic?

Run pip install jentic, search Jentic for 'list CUDO Compute virtual machines', load the schema for the /v1/projects/{projectId}/vms list operation, and execute it with the project ID. Jentic injects the bearer token from MAXsystem so the agent never handles the raw key.

How do I track spend on a CUDO billing account?

Call GET /v1/billing-accounts/{billingAccountId}/spend/details. The response gives a breakdown of usage and cost so a cost-aware agent can decide whether to launch more VMs within the day's budget.

Is the CUDO Compute API free?

The API itself is free to call once you have a CUDO account. Charges come from the underlying compute, storage, and network resources on a usage-based pricing model published in the CUDO Compute console.