VoltageGPU MCP server
Commit Nov 6, 2026Deploy and manage confidential VMs and standard GPU pods with Intel TDX and NVIDIA attestation via a command-line interface or Python SDK.
Also known as VoltageGPU/VOLTAGEGPU-CLI
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What is VoltageGPU MCP?
VoltageGPU deploys and manage confidential VMs and standard GPU pods with Intel TDX and NVIDIA attestation via a command-line interface or Python SDK.
Summary generated from the project's README
About VoltageGPU MCP server
VOLTAGEGPU-CLI provides a command-line interface and Python SDK to deploy and manage high-performance computing resources. Developers can provision standard GPU pods for general workloads or confidential VMs that utilize Intel TDX and NVIDIA attestation for sensitive tasks. The tool allows for precise control over machine selection, including filtering by GPU model or maximum price.
Users interact with the service via the voltagegpu command or the shorter vgpu alias. Setup requires an API key and registered SSH keys for secure access. The system supports local execution through an MCP server for AI agents, which uses stdio to provide tools like ls, up, ps, and exec. This local setup ensures that private SSH keys remain on the user machine while allowing agents to manage infrastructure. Billing is calculated per second, and the CLI includes built-in safeguards like mandatory time-to-live settings to prevent unexpected costs.
What you can do with it
- 1Deploy cheapest available GPUFind and launch the most affordable standard machine with a specific GPU model.
- 2Verify confidential hardware integrityRun an attestation check to ensure a confidential VM is running on trusted Intel TDX and NVIDIA hardware.
- 3Automate infrastructure via AI agentsConnect an AI client to the local MCP server to manage pods using tools like list, up, and remove.
- 4Execute remote commands securelyRun a specific command on a running pod and retrieve the exit code without an interactive shell.
Written from the project's README. Every use case is checked against a quote from it.
Configuration
VOLT_API_KEY
| Name | Description | |
|---|---|---|
| VOLT_API_KEY | — |
Automated checks
Ran Nov 15, 2026Full report →Not verified yet. A server needs a score of 80, no serious finding, and enough data for us to check. How checks work · What to fix for more points
- Source repository linked and reachablevoltagegpu/voltagegpu-cli is public and reachablegithub.com/voltagegpu/voltagegpu-cli ↗Pass
- Package names this repository as its sourceNot checked
- Build provenance (Sigstore attestation)Not checked
- Open source license (OSI)MITspdx.org/licenses/MIT.html ↗Pass
- Commit or release in the last yearLast commit or release 2026-11-06github.com/voltagegpu/voltagegpu-cli ↗Pass
- OpenSSF ScorecardNot checked
- Package name not close to a popular packageNot checked
- No critical advisory in the package or its dependenciesNot checked
- No hidden instructions to the model0 tool descriptions and the README read; no override phrases, credential paths or hidden charactersPass
- Destructive tools are labelledNot checked
- Remote endpoint answers the MCP handshakeNot checked
README
View on GitHubvoltagegpu-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 questions
How is VoltageGPU billed?
Billing is performed per second. For the first hour, you are charged upon deployment, but if you stop a standard pod, the unused portion of that hour is returned to your balance.
How do I log in to the CLI?
You can create an API key on their website and then run 'voltagegpu login' to prompt for the key, or export the VOLT_API_KEY environment variable for scripts.
Can I use the VoltageGPU MCP server with Claude?
Yes, you can add it to Claude Code using the command 'claude mcp add voltagegpu -e VOLT_API_KEY=volt_... -- vgpu mcp'.
What is the difference between Confidential VMs and standard pods?
Confidential VMs use Intel TDX trust domains with NVIDIA GPUs and allow for self-generated attestation, while standard pods are whole GPU machines without an enclave for non-sensitive workloads.