ComputeNexa
PYPI · COMPUTENEXA-MCP
Find, launch and stop private GPUs on ComputeNexa, with a quote before anything is charged.
Available components
Last scanned (12 hours ago)
Scores higher than 81% of PyPI servers
Category Cloud Infrastructure
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security100
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs hatchling.build at install time, a recognised build step with no custom scripting around it. View diagnostics → Pass
- 1 of 32 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency100
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Cryptographically verified build provenance (signed, bound to computenexa-gpuInfrastructure/computenexa-mcp). View diagnostics → Pass
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 5 days ago).Pass
- Publishes a security disclosure policy (SECURITY.md).Pass
Schema Quality & AI Usability70
- AI-judged instruction clarity (good).Pass
- Tool/resource definitions use about 1357 tokens (~90/item across 15 items; 15 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management0
- Stability not yet verified: not enough scan history yet (needs a 30-day window).Unverified
Tool Coverage95
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 83% of tool parameters carry a description.Partial
- Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 15 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 16 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a current MCP spec version (2026-07-28).Pass
Unverified: 1 category
A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.
Checks we ran (15)
- Malware scan
- Known CVEs
- Install scripts
- Dependency health
- Source repository
- Provenance
- License
- Maintenance
- Security disclosure
- Schema quality
- Tool coverage
- Injection markers
- Destructive annotations
- Judged manipulation
- MCP protocol
Checks we could not complete (1)
These are gaps on our side, not findings about this package. We only credit what we can confirm, so a category made up entirely of them scores 0.
- Stability in Stability & Change Management (scores 0 for this)Stability not yet verified: not enough scan history yet (needs a 30-day window).
Does not apply to this package (2)
- Endpoint SecurityScored on hosted endpoints only. A package has no live endpoint of its own for us to probe.
- Transport & ReachabilityScored on hosted endpoints only. A package has no live endpoint of its own for us to probe.
The score does not measure everything. What the score does not measure →
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 2 Nov 26 +15
- Malware scan: unverified → pass ▲ security
- 1 Nov 26 65
First indexed and scored.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 6 Nov 2026 · Analysed pypi/computenexa-mcp@0.1.0
Provenance Verified
A signed build attestation was found and verified, binding this exact artifact to the source repository it claims to come from.
| Result | Verified |
|---|---|
| Ecosystem | pypi |
| Reason | Verified |
| Discovered via | Registry attestation endpoint |
| Source repo | computenexa-gpuInfrastructure/computenexa-mcp |
| Certificate issuer | https://token.actions.githubusercontent.com |
| Certificate SAN | https://github.com/computenexa-gpuInfrastructure/computenexa-mcp/.github/workflows/publish.yml@refs/tags/v0.1.0 |
| Rekor log index | 3616437461 |
| Predicate type | PyPI publish attestation https://docs.pypi.org/attestations/publish/v1 |
| Subject digest | sha256:f6cfebbe5bb24e3ab5c0315bcf6e65121a337453c2f9147c23ab6dbfa2039629 |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | Known build tool | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Dependencies 32 packages
| Packages resolved | 32 |
|---|---|
| No linked repository | 1 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
create_endpoint Create an endpoint ~82
A new Endpoint (owners and admins): a stable HTTPS address and key for your own server on port 8000, e.g. one per customer you serve. Launch machines for it with launch_machine(endpoint=...). Free. Its key is shown once here; get_endpoint_key shows it again.
| Name | Type | Req | Description |
|---|---|---|---|
| name | string | yes | e.g. the customer it serves |
| Name | Type | Req | Description |
|---|---|---|---|
| id | string | yes | – |
| key | – | – | Only when just created, or from get_endpoint_key |
| machine | – | yes | The machine it points at now, if any |
| name | string | yes | – |
| url | string | yes | – |
No examples provided.
extend_machine Extend a machine ~98
Add time to a machine at the price it launched with. Costs money: quote first (confirm=false), then confirm=true with expected_total_usd once the person agrees.
| Name | Type | Req | Description |
|---|---|---|---|
| confirm | boolean | – | false = only quote; true = extend, after the person agreed |
| expected_total_usd | – | – | With confirm=true: the quoted total_usd |
| hours | number | yes | Time to add |
| machine_id | string | yes | – |
| Name | Type | Req | Description |
|---|---|---|---|
| machine | – | – | – |
| quote | – | – | – |
| status | string | yes | quote = nothing happened yet; done = it was carried out |
No examples provided.
get_endpoint_key Get an endpoint's key ~45
An Endpoint's key (owners and admins). Only when the person asks for it: it gives access to their server.
| Name | Type | Req | Description |
|---|---|---|---|
| endpoint | string | yes | Endpoint name or id |
| Name | Type | Req | Description |
|---|---|---|---|
| endpoint | string | yes | – |
| key | string | yes | – |
| url | string | yes | – |
No examples provided.
get_machine Get a machine ~62
One machine: its state, how to connect (SSH command, browser apps, API or endpoint address), time left, keep-running status and costs. Never its keys.
| Name | Type | Req | Description |
|---|---|---|---|
| machine_id | string | yes | e.g. cnx-7f3a9c |
| Name | Type | Req | Description |
|---|---|---|---|
| api_base_url | – | – | Model API / Voice Agent machines: their API address |
| app | string | yes | – |
| billing | – | – | – |
| browser_apps | array | – | Apps to open from the dashboard's Open button while running |
| charged_usd | number | yes | – |
| cost_so_far_usd | number | yes | What it costs if it ended now |
| end_reason | – | – | – |
| endpoint_name | – | – | – |
| endpoint_url | – | – | Your own server on the machine's port 8000 |
| expires_at | – | yes | – |
| gpu | string | yes | – |
| gpu_count | integer | yes | – |
| id | string | yes | e.g. cnx-7f3a9c |
| keep_running_hours | – | yes | Renews this many hours at a time; null = off |
| label | – | yes | – |
| launched_by | – | – | – |
| model | – | – | – |
| next_renewal_at | – | – | – |
| price_per_hour_usd | number | yes | For the whole machine (all its GPUs) |
| project | – | – | – |
| refunded_usd | number | yes | – |
| region | – | – | – |
| renew_failed | boolean | – | – |
| ssh_command | – | yes | While running, if the machine has an SSH key |
| startup_progress | – | – | – |
| state | string | yes | requested | provisioning | running | stopping | terminated | failed |
| time_left_minutes | – | yes | – |
No examples provided.
get_usage Get usage ~38
Spending and GPU-hours over the last N days, by GPU, app, day and project.
| Name | Type | Req | Description |
|---|---|---|---|
| days | integer | – | The last N days |
| Name | Type | Req | Description |
|---|---|---|---|
| balance_usd | number | yes | – |
| by_app | array | yes | – |
| by_gpu | array | yes | – |
| daily | array | yes | – |
| days | integer | yes | – |
| gpu_hours | number | yes | – |
| projects | array | yes | – |
| sessions | integer | yes | – |
| spend_usd | number | yes | – |
| topups_usd | number | yes | – |
No examples provided.
launch_machine Launch a machine ~264
Launch a GPU machine. Costs money: call first with confirm=false to get a quote (nothing happens), show it to the person, and only after they agree call again with the same arguments, confirm=true and expected_total_usd. The booked time is charged up front from the team's balance.
| Name | Type | Req | Description |
|---|---|---|---|
| app | string | yes | App from list_apps, e.g. datascience |
| confirm | boolean | – | false = only quote (default); true = launch, after the person agreed to the quote |
| endpoint | – | – | Endpoint name or id this machine serves |
| expected_total_usd | – | – | With confirm=true: the quote's total_usd the person agreed to |
| gpu | string | yes | GPU slug from list_gpus, e.g. rtx-a6000 |
| gpu_count | integer | – | – |
| hours | number | yes | How long to book; unused time is refunded |
| keep_running_hours | – | – | Renew this many hours at a time until stopped |
| label | – | – | A name for the machine |
| model | – | – | For apps with models; left out = our recommendation for this GPU |
| project | – | – | Project name or id to restore into ~/work and save back |
| region | string | – | Where it must run |
| Name | Type | Req | Description |
|---|---|---|---|
| machine | – | – | – |
| quote | – | – | – |
| status | string | yes | quote = nothing happened yet; done = it was carried out |
No examples provided.
list_apps List apps ~93
The apps a GPU can start with (basic, datascience, chat, imagegen, modelapi, voice): what each is for, the models it offers and which model we recommend per GPU memory. Give `app` for the software installed.
| Name | Type | Req | Description |
|---|---|---|---|
| app | – | – | One app, to also see what's installed in it |
| package | – | – | With app: find this package's version, e.g. torch |
| Name | Type | Req | Description |
|---|---|---|---|
| apps | array | yes | – |
| software | array | – | What's installed (when one app was asked for) |
No examples provided.
list_endpoints List endpoints ~41
Endpoints: stable HTTPS addresses for your own server on a machine's port 8000, and the machine each points at now. Never their keys.
Input schema present but exposes no named parameters.
| Name | Type | Req | Description |
|---|---|---|---|
| endpoints | array | yes | – |
No examples provided.
list_gpus List GPUs ~95
GPUs with live prices (US dollars per GPU per hour) and stock, cheapest first.
| Name | Type | Req | Description |
|---|---|---|---|
| app | – | – | Only GPUs that run this app (see list_apps), e.g. chat |
| include_sold_out | boolean | – | Also list GPUs not for sale right now |
| min_memory_gb | – | – | At least this much GPU memory |
| region | string | – | any = anywhere; us; ca = Canada |
| Name | Type | Req | Description |
|---|---|---|---|
| gpus | array | yes | – |
| region | string | yes | – |
No examples provided.
list_machines List machines ~66
Your machines, newest first: state, GPU, app, price, time left and cost so far.
| Name | Type | Req | Description |
|---|---|---|---|
| active_only | boolean | – | Only starting or running machines |
| limit | integer | – | – |
| whole_team | boolean | – | The whole team's machines (owners and admins) |
| Name | Type | Req | Description |
|---|---|---|---|
| machines | array | yes | – |
No examples provided.
list_projects List projects ~26
Saved projects (files restored into ~/work on machines launched with them) and their size.
Input schema present but exposes no named parameters.
| Name | Type | Req | Description |
|---|---|---|---|
| projects | array | yes | – |
No examples provided.
list_receipts List receipts ~45
Finished sessions and what each cost in the end (charged minus refunded).
| Name | Type | Req | Description |
|---|---|---|---|
| days | integer | – | Sessions that ended in the last N days |
| limit | integer | – | – |
| Name | Type | Req | Description |
|---|---|---|---|
| receipts | array | yes | – |
| total_net_usd | number | yes | – |
No examples provided.
set_keep_running Keep a machine running ~148
Keep running: the machine renews itself `hours` at a time from the team's balance, at its launch price, until it's stopped. Turning it on spends money at every renewal: quote first, then confirm=true with expected_renewal_usd. Turning it off (hours=null) needs no confirmation.
| Name | Type | Req | Description |
|---|---|---|---|
| confirm | boolean | – | Turning on: false = only quote; true = turn on, after the person agreed |
| expected_renewal_usd | – | – | With confirm=true: the quoted renewal_usd |
| hours | – | yes | Renew this many hours at a time; null = turn off (it stops when its paid time ends) |
| machine_id | string | yes | – |
| Name | Type | Req | Description |
|---|---|---|---|
| machine | – | – | – |
| quote | – | – | – |
| status | string | yes | quote = nothing happened yet; done = it was carried out |
No examples provided.
stop_machine Stop a machine ~58
End a machine now: stopped if running, cancelled with a full refund if still starting. Files outside a project are deleted; a project is saved first. Unused time is refunded. Can't be undone.
| Name | Type | Req | Description |
|---|---|---|---|
| machine_id | string | yes | – |
| Name | Type | Req | Description |
|---|---|---|---|
| machine | – | yes | – |
| refunded_usd | number | yes | – |
No examples provided.
whoami Who am I ~41
Who this server's API key acts as: email, team and role, the team's balance and GPU limit, and whether the key may launch and stop machines.
Input schema present but exposes no named parameters.
| Name | Type | Req | Description |
|---|---|---|---|
| api_key | – | yes | The key this server uses; null if the platform doesn't report it |
| balance_usd | number | yes | The team's prepaid balance |
| can_launch | – | yes | Whether this server's key may launch, extend and stop machines |
| string | yes | – | |
| gpu_limit | integer | yes | GPUs the team may run at the same time |
| role | – | yes | Your role in the team: owner, admin or member |
| team | – | yes | – |
| team_members | – | yes | – |
No examples provided.
How do I install the ComputeNexa MCP server?
ComputeNexa runs locally as a PyPI package, launched with uvx computenexa-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · computenexa-mcp
claude mcp add computenexa-gpuinfrastructure-computenexa-mcp -- uvx computenexa-mcp
What is the ComputeNexa MCP server?
ComputeNexa is an MCP server listed in the public MCP registry as io.github.computenexa-gpuInfrastructure/computenexa-mcp. Find, launch and stop private GPUs on ComputeNexa, with a quote before anything is charged. This page covers its PyPI package (computenexa-mcp).
Is the ComputeNexa MCP server safe to use?
ComputeNexa scores 80 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 6 November 2026. Its build provenance is signed and verified. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the ComputeNexa MCP server expose?
ComputeNexa exposes 15 tools: whoami, list_gpus, list_apps, list_machines, get_machine, and 10 more. Their descriptions and schemas cost roughly 1,202 tokens of context every time the server is loaded.
Is the ComputeNexa MCP server still maintained?
ComputeNexa is still listed as active in the MCP registry. We last reached this channel on 6 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the ComputeNexa MCP server under?
ComputeNexa declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.
What did VerifyMCP test on the ComputeNexa MCP server?
VerifyMCP ran 15 checks on ComputeNexa, covering Malware scan, Known CVEs, Install scripts, Dependency health and 11 more. One item could not be completed, a gap on our side rather than a finding about ComputeNexa: Stability. One category scores 0 for that reason, because we only credit what we can confirm. Endpoint Security and Transport & Reachability do not apply to a PyPI package, so they were not tested. The score does not measure everything, and the scoring documentation lists what it leaves out.