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Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
NOSANA_API_KEYNoYour Nosana API key. Can be omitted if you have already run `nosana-deploy login`, in which case the key is read from `~/.config/nosana-deploy/config.json`.

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}
prompts
{
  "listChanged": true
}
resources
{
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
get_balanceA

Credits on the Nosana account behind the API key: assigned, reserved by running deployments, settled (spent) and available. 1 credit is priced like 1 USD.

list_templatesA

Ready-to-run Nosana templates (MiniMax H3 video, Qwen and Gemma models via Ollama, ComfyUI, Jupyter, VS Code, Whisper, ...). Templates with variants need a variant id when deploying.

get_templateA

Details of one template or variant: VRAM needed, hardware notes (e.g. MiniMax H3 needs a Blackwell GPU), whether it exposes a web endpoint, variants, and optionally the job definition it deploys.

list_gpusA

GPU markets with price per hour (network fee included, matches deploy.nosana.com), idle hosts available right now, VRAM, and, when a template is given, whether each GPU fits it.

estimate_deploymentA

Dry run: resolve the template/variant and GPU, validate the plan, and return the cost in credits for one timeout window plus warnings (too little VRAM, non-Blackwell card, insufficient credits, no idle hosts). Nothing is created. Call this before create_deployment and show the user the cost.

create_deploymentA

SPENDS CREDITS. Creates a Nosana deployment from a template or job definition on the chosen GPU and starts it. Requires confirm=true, which you must only pass after the user has seen the estimate from estimate_deployment and agreed. Returns the deployment id; then poll wait_for_deployment until the endpoint is ready or the job completes.

wait_for_deploymentA

Blocks up to max_seconds (default 60, max 120) watching a deployment. Returns outcome "online" (service answers; includes ready URLs), "completed" (job finished; includes logs), "failed" (with the scheduler error), or "pending" (call again). Safe to call repeatedly.

get_deploymentA

Current status of a deployment with endpoints (tunnel online and whether the service actually answers), recent jobs and recent events.

list_deploymentsB

Deployments on this account (newest first) with status, strategy, active jobs and timeout.

stop_deploymentA

Stops a deployment and its running jobs. Billing stops with them. Use when the user is done or when a deployment can never schedule.

start_deploymentA

SPENDS CREDITS. Starts a DRAFT or STOPPED deployment again with its existing settings. Requires confirm=true after the user agreed.

extend_deploymentA

Sets a new timeout in minutes for a deployment (minimum 60). Longer timeouts reserve more credits.

get_job_resultB

Logs and results of a deployment job (latest job by default).

get_deployment_eventsA

Scheduler event log for a deployment (job listed, stopped, errors such as insufficient funds or bad timeout). Newest first.

Prompts

Interactive templates invoked by user choice

NameDescription
deploy_minimax_h3Guided flow: check credits, pick the variant and GPU, estimate, confirm, deploy, and hand back the ComfyUI URL.

Resources

Contextual data attached and managed by the client

NameDescription
templatesReady-to-run template catalog with variants and VRAM needs.
gpusGPU markets with price per hour and idle hosts right now.

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