VoltageGPU MCP server
Commit 6. Nov. 2026Deploye und verwalte vertrauliche VMs und Standard-GPU-Pods mit Intel TDX und NVIDIA Attestation über ein CLI oder ein Python SDK.
Auch bekannt als VoltageGPU/VOLTAGEGPU-CLI
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Was ist VoltageGPU MCP?
VoltageGPU ist ein MCP server. Deploye und verwalte vertrauliche VMs und Standard-GPU-Pods mit Intel TDX und NVIDIA Attestation über ein CLI oder ein Python SDK.
Zusammenfassung generiert aus dem README des Projekts
Über VoltageGPU MCP server
VOLTAGEGPU-CLI bietet ein Command-Line Interface und ein Python SDK, um High-Performance-Computing-Ressourcen bereitzustellen und zu verwalten. Entwickler können Standard-GPU-Pods für allgemeine Workloads oder Confidential VMs bereitstellen, die Intel TDX und NVIDIA Attestation für sensible Aufgaben nutzen. Das Tool ermöglicht eine präzise Kontrolle bei der Maschinenauswahl, einschließlich Filtern nach GPU-Modell oder maximalem Preis.
Nutzer interagieren mit dem Service über den Befehl 'voltagegpu' oder den kürzeren Alias 'vgpu'. Für das Setup sind ein API-Key und registrierte SSH-Keys für den sicheren Zugriff erforderlich. Das System unterstützt die lokale Ausführung über einen MCP server für AI Agents, der stdio nutzt, um Tools wie ls, up, ps und exec bereitzustellen. Dieses lokale Setup stellt sicher, dass private SSH-Keys auf der Maschine des Nutzers bleiben, während Agents die Infrastruktur verwalten können. Die Abrechnung erfolgt pro Sekunde, und das CLI enthält integrierte Sicherheitsmechanismen wie obligatorische Time-to-Live-Einstellungen, um unerwartete Kosten zu vermeiden.
Was du damit machen kannst
- 1Günstigste verfügbare GPU deployenFinde und starte die preiswerteste Standard-Maschine mit einem spezifischen GPU-Modell.
- 2Integrität der vertraulichen Hardware verifizierenFühre einen Attestation-Check durch, um sicherzustellen, dass eine Confidential VM auf vertrauenswürdiger Intel TDX und NVIDIA Hardware läuft.
- 3Infrastruktur via AI Agents automatisierenVerbinde einen AI-Client mit dem lokalen MCP server, um Pods mit Tools wie list, up und remove zu verwalten.
- 4Remote-Befehle sicher ausführenFühre einen spezifischen Befehl auf einem laufenden Pod aus und erhalte den Exit-Code ohne eine interaktive Shell.
Geschrieben aus dem README des Projekts. Jeder Use Case wurde gegen ein Zitat daraus geprüft.
Konfiguration
VOLT_API_KEY
| Name | Beschreibung | Typ |
|---|---|---|
| VOLT_API_KEY | — |
Automatisierte Checks
Geluften am 15. Nov. 2026Vollständiger Bericht →Noch nicht verifiziert. Ein Server benötigt einen Score von 80, keine kritischen Befunde und genug Daten für unsere Prüfung. Wie die Checks funktionieren · Was du für mehr Punkte verbessern kannst
- Source Repository verknüpft und erreichbarvoltagegpu/voltagegpu-cli is public and reachablegithub.com/voltagegpu/voltagegpu-cli ↗Bestanden
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- Open Source Lizenz (OSI)MITspdx.org/licenses/MIT.html ↗Bestanden
- Commit oder Release im letzten JahrLast commit or release 2026-11-06github.com/voltagegpu/voltagegpu-cli ↗Bestanden
- OpenSSF ScorecardNicht geprüft
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- Remote-Endpoint beantwortet den MCP-HandshakeNicht geprüft
README
Auf GitHub ansehenvoltagegpu-cli
Deploy and manage VoltageGPU machines from your terminal or from Python:
- Confidential VMs: Intel TDX trust domains with an NVIDIA GPU, only your SSH keys on the machine, and an attestation you generate and verify yourself.
- Standard pods: whole GPU machines without an enclave, for workloads that are not sensitive.
Billing is per second. The first hour is charged when you deploy; when you stop a standard pod, the unused part of that hour goes back to your balance.
pip install voltagegpu-cli
Python 3.10 or newer. The package installs the voltagegpu command (volt is
an alias kept from earlier releases).
1. Log in
Create an API key at https://voltagegpu.com/api-keys (it is shown once), then:
voltagegpu login # prompts for the key, hidden, checks it, saves it to ~/.volt/config.ini (mode 0600)
# or, for CI and scripts:
export VOLT_API_KEY=volt_...
Add the SSH key you will connect with (defaults to ~/.ssh/id_ed25519.pub):
voltagegpu ssh-keys add
voltagegpu ssh-keys list
2. Pick a machine
voltagegpu machines # Confidential VM tiers, then standard machines, cheapest first
voltagegpu machines --standard --gpu A6000 # filter by GPU model
voltagegpu machines --standard --max-price 1 --json
voltagegpu machines --confidential
voltagegpu templates # images for standard pods (PyTorch by default)
3a. Deploy a standard pod
voltagegpu deploy standard --machine <machine_id>
voltagegpu deploy standard --cheapest --gpu 4090 --wait # cheapest matching machine, wait for SSH
The CLI shows the price and asks before charging. In scripts, add --yes.
If your account has several SSH keys, choose one with --ssh-key <key_id>.
Other options: --template <template_id>, --jupyter, --ports 3,
--auto-terminate 8 (hours), --name my-pod.
3b. Deploy a Confidential VM
voltagegpu deploy confidential --tier rtx6000b-small --wait
voltagegpu deploy confidential --tier h100-small --hardstop 4 --port 8000 --port 8443/tcp
Every SSH key on your account is bound to the VM when it is created; a VM cannot be given a key afterwards, so add yours first. The sudo password is printed once and is not kept anywhere. The command also prints how to generate the attestation inside the VM.
4. Connect, inspect, stop
voltagegpu pods list
voltagegpu pods wait <pod_id> # until SSH answers
voltagegpu ssh <pod_id> # interactive shell
voltagegpu ssh <pod_id> -- nvidia-smi -L # run one command
voltagegpu ssh <pod_id> --print # just print the ssh command
voltagegpu pods show <pod_id>
voltagegpu pods stop <pod_id> # releases it: billing stops, the disk is deleted
voltagegpu balance
Fresh pods present a new host key. In non-interactive scripts you can accept it
on first use with -o StrictHostKeyChecking=accept-new.
5. Verify a Confidential VM
Inside the VM you produce an evidence bundle (the deploy output prints the exact commands). On your own machine:
pip install "voltagegpu-cli[verify]" # installs voltage-verify
voltagegpu verify bundle.json --challenge <hex-you-issued> --gpus 1
voltagegpu verify bundle.json --challenge <hex-you-issued> --offline --accept-offline-tcb
voltagegpu verify runs voltage-verify,
which checks the Intel TDX quote up to Intel's root and the NVIDIA GPU
attestation tokens, without trusting VoltageGPU. Online, the TCB status and
revocation are checked against Intel's collateral of today. --offline uses
the Intel collateral inside the bundle: the verdict names that limit and the
exit code is 3, unless --accept-offline-tcb (voltage-verify 0.3.0 or later).
voltagegpu verify returns voltage-verify's own exit code.
Scripting
Every list command takes --json; deploys and stops take --yes.
# Deploy the cheapest standard machine, wait for SSH, run a job, release it.
POD=$(voltagegpu deploy standard --cheapest --max-price 1 --yes --json | jq -r .deploy.pod_id)
voltagegpu pods wait "$POD"
voltagegpu ssh "$POD" -o StrictHostKeyChecking=accept-new -- nvidia-smi
voltagegpu pods stop "$POD" --yes
Exit codes: 0 success, 1 API or runtime error, 2 usage error or missing
confirmation.
vgpu: the short command for scripts and AI agents
Installed with the package, next to voltagegpu. The key comes from
VOLT_API_KEY or VOLTAGEGPU_API_KEY (or voltagegpu login) and is never
printed. Give an agent a limited key (scopes, its own machines only, a
daily budget) from https://voltagegpu.com/api-keys, never your full key.
vgpu ls --json # every offer, cheapest first
vgpu ls --kind vm --gpu H100 # vm | cpu | standard | baremetal | sandbox
vgpu up rtx6000b-small --name train1 --ttl 2h -y --json
vgpu ps --json
vgpu exec train1 "nvidia-smi" # returns the remote exit code
vgpu exec train1 -d "python train.py" # background: prints PID and log path
vgpu scp train1 /home/ubuntu/out.tgz ./out.tgz # --up to copy the other way
vgpu attest train1 # Confidential VM or Confidential CPU only
vgpu rm train1 -y
vgpu whoami # scopes, budgets, spend, balance
vgpu mcp # local MCP server (stdio) for agents
--ttl is mandatory and becomes the auto-stop of each product, rounded up,
refused locally when out of bounds: Confidential VM and CPU up to 720h,
standard pods 1h to 720h (whole hours), dedicated machines 1h to 72h (whole
hours), sandboxes up to 7d. up asks for confirmation unless -y is given,
and fails without -y when not run in a terminal. A deploy that gets no
answer is never retried: run vgpu ps first.
exec, scp and attest use your local SSH key (-i, or VGPU_SSH_KEY).
The first connection to a machine records its host key in
~/.volt/known_hosts.d/<id> (trust on first use); a changed key is refused.
Names given at up are kept in ~/.volt/vgpu-names.json; ids work too.
Confidential VMs and CPU tiers bind the SSH keys already on the account.
A standard GPU binds one key: the account's only key, or --ssh-key-id ID
when the account has several (voltagegpu ssh-keys list shows the ids).
Dedicated machines and sandboxes take key ids: by default every key of the
account, but a key limited to its own machines cannot read them, so pass
--ssh-key-id ID (repeatable). For such a key whoami and voltagegpu balance show the balance as hidden: only a full key reads it.
vgpu attest draws a challenge on your machine, runs the published proof
script in the machine (two-proofs-in-the-vm.sh for a Confidential VM,
snp-proof-in-the-vm.sh for a Confidential CPU tier, both embedded and pinned
by SHA-256), copies the archive back and verifies it here: voltage-verify
for Intel TDX + NVIDIA (pip install 'voltagegpu-cli[verify]'). --offline
verifies without network, with the Intel collateral inside the bundle: the TCB
and revocation are then not checked against Intel today, so the result stays
VERIFIED but names that limit (limits in --json) and exits with 10,
unless --accept-offline-tcb. For SEV-SNP: the report is requested at --vmpl (0 by
default, sent as SNP_VMPL; if VMPL 0 is refused, the script says so and asks
again at 1, and the result reports it), REPORT_DATA equals the challenge, the
report policy forbids debug and its VMPL field is the level requested (the
guest kernel uses VMPCK0, consistent with VMPL 0, no SVSM), then the AMD chain and the VCEK are
fetched again from AMD into a new folder (snpguest 0.11.0 fetch ca / fetch vcek on your machine), the ARK must be one of the AMD roots pinned in the
script, and snpguest verify certs / verify attestation run with those
certificates, never the ones in the archive (they come from the VM). Without
a local snpguest, or when the AMD key server cannot be reached, the result
is INCOMPLETE, never VERIFIED. Standard pods, dedicated machines and sandboxes have no tenant
attestation and are refused.
| Exit code | Meaning |
|---|---|
| 0 | ok |
| 1 | error (including a deploy that got no answer) |
| 2 | usage: bad option, --ttl out of bounds, missing -y |
| 3 | API key missing, malformed or refused |
| 4 | API key scope missing (API_KEY_SCOPE_MISSING), or account resource refused to a key limited to its own machines (API_KEY_ACCOUNT_RESOURCE) |
| 5 | not found (machine or tier) |
| 6 | balance too low or API key budget exceeded (API_KEY_BUDGET_EXCEEDED, HTTP 402): stop, nothing was charged |
| 7 | unavailable: sold out, over --max-price, rate limited, offer closed |
| 8 | attestation failed |
| 9 | attestation incomplete, or a local tool is missing (ssh, scp, voltage-verify) |
| 10 | attestation verified with a limit: --offline, TCB and revocation not checked against Intel today (--accept-offline-tcb accepts it; local MCP server: ATTESTATION_LIMITED) |
With --json, an error is also printed on stdout as
{"error": {"code", "message", "exit_code", ...}}.
Local MCP server
vgpu mcp serves the tools ls, up, ps, exec, scp, rm, attest,
inference and whoami over stdio. It runs on your machine because exec,
scp and attest use your SSH private key, which never leaves it. Same
guards as the command line: up requires ttl and max_hourly_price, rm
requires confirm: true, a 402 comes back as API_KEY_BUDGET_EXCEEDED with
"do not retry", the key is never part of an answer, and the sudo password of
a Confidential VM is never handed to the agent. inference calls the
OpenAI-compatible API with an inference key (vgpu_...) in
VOLTAGEGPU_API_KEY; a vgpu_ value there is never sent to the pod API,
which takes the volt_ key from VOLT_API_KEY.
claude mcp add voltagegpu -e VOLT_API_KEY=volt_... -- vgpu mcp # Claude Code
# Codex: ~/.codex/config.toml
[mcp_servers.voltagegpu]
command = "vgpu"
args = ["mcp"]
env = { VOLT_API_KEY = "volt_..." }
Python SDK
from volt.sdk import VoltageGPUClient
with VoltageGPUClient() as client: # VOLT_API_KEY or ~/.volt/config.ini
machine = client.list_machines("standard")[0] # cheapest first
result = client.deploy_standard(machine.id, name="my-pod")
pod = client.wait_until_reachable(result.pod_id)
print(pod.ssh_command)
print(client.release_pod(result.pod_id).prepaid_refund)
A complete example is in examples/deploy_standard_pod.py.
REST API
The CLI is a thin client of the public API, documented at https://docs.voltagegpu.com/api-reference. The same deploy with curl:
curl -X POST https://api.voltagegpu.com/api/volt/pods \
-H "X-API-Key: $VOLT_API_KEY" -H "Content-Type: application/json" \
-d '{"provider":"standard","name":"my-pod","machine_id":"<machine_id>"}'
curl https://api.voltagegpu.com/api/volt/pods -H "X-API-Key: $VOLT_API_KEY"
Configuration
| Setting | Where |
|---|---|
| API key | --api-key of login, VOLT_API_KEY (or VOLTAGEGPU_API_KEY), then ~/.volt/config.ini |
| API base URL | VOLT_BASE_URL (https only, voltagegpu.com hosts unless VOLT_ALLOW_CUSTOM_BASE_URL=1; default https://api.voltagegpu.com/api) |
| Debug | VOLT_DEBUG=1 shows tracebacks |
voltagegpu config shows where the key comes from, masked.
Security
- The key is sent only over HTTPS, in the
X-API-Keyheader; redirects are never followed and certificates are always verified. - The key is never printed.
~/.volt/config.iniis created readable by you only, andvoltagegpu configwarns if its permissions are too open. - The SSH command returned by the API is parsed into user, host and port, only that rebuilt form is ever shown, and ssh is started without a shell (and never from the current directory), so a tampered answer cannot run a command on your machine. Server text is printed literally, without terminal escapes.
ssh-keys addrefuses private keys.
Report a vulnerability to contact@voltagegpu.com.
Upgrading from 1.2
volt cc inventory/volt cc deploy: Confidential containers were retired on 2026-10-01. Usevoltagegpu machines --confidentialandvoltagegpu deploy confidential --tier <tier>.volt pods stopnow releases the pod and reports the refund.volt account balanceis nowvoltagegpu balance.
Links
- Docs: https://docs.voltagegpu.com/cli
- API reference: https://docs.voltagegpu.com/api-reference
- API keys: https://voltagegpu.com/api-keys
- Changelog: CHANGELOG.md
MIT License.
VoltageGPU MCP Fragen
Wie wird VoltageGPU abgerechnet?
Die Abrechnung erfolgt pro Sekunde. Für die erste Stunde wird der Betrag direkt bei der Bereitstellung berechnet, aber wenn du einen Standard-Pod stoppst, wird der ungenutzte Teil dieser Stunde deinem Guthaben wieder gutgeschrieben.
Wie logge ich mich im CLI ein?
Du kannst auf der Website einen API-Key erstellen und dann 'voltagegpu login' ausführen, um zur Eingabe des Keys aufgefordert zu werden, oder die Umgebungsvariable VOLT_API_KEY für Skripte exportieren.
Kann ich den VoltageGPU MCP server mit Claude nutzen?
Ja, du kannst ihn mit dem Befehl 'claude mcp add voltagegpu -e VOLT_API_KEY=volt_... -- vgpu mcp' zu Claude Code hinzufügen.
Was ist der Unterschied zwischen Confidential VMs und Standard-Pods?
Confidential VMs nutzen Intel TDX Trust Domains mit NVIDIA GPUs und ermöglichen eine selbst generierte Attestation, während Standard-Pods komplette GPU-Maschinen ohne Enclave für nicht-sensible Workloads sind.