Lium GPU Cloud
PYPI · LIUM.IO
Rent NVIDIA GPU pods on Lium, run commands on them and remove them, billed per second.
Available components
Last scanned (3 hours ago)
Scores higher than 73% 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 Security99
- No malware found by supply-chain analysis.Pass
- Known CVEs were checked across the 49 of 50 dependencies we could resolve, so this covers what we could see, not the whole tree.Partial
- Runs hatchling.build at install time, a recognised build step with no custom scripting around it. View diagnostics → Pass
- Dependency health was assessed across the 49 of 50 dependencies we could resolve, so this covers what we could see, not the whole tree. View diagnostics → Partial
Provenance & Transparency97
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Cryptographically verified build provenance (signed, bound to Datura-ai/lium). View diagnostics → Pass
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 0 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability71
- AI-judged instruction clarity (good).Pass
- Tool/resource definitions use about 653 tokens (~108/item across 6 items; 6 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management10
- Stability observed for 3 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage71
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 0% of tool parameters carry a description.Fail
- Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety75
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- 0 of 1 tool(s) whose name or description implies an irreversible operation declare an MCP destructiveHint annotation; "remove_pod" implies "remove" and declares no destructiveHint at all, which the MCP spec reads as destructive by default. See how to fix → Fail
- An AI judge read all 7 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
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.
- 23 Oct 26 0
- Package version: 0.28.0 → 0.28.1 functional
- 22 Oct 26 +1
- Malware scan: pass → unverified ▼ security
- Package version: 0.26.0 → 0.28.0 functional
- Package version: 0.26.0 → 0.27.2 functional
- 21 Oct 26 +15
- Malware scan: unverified → pass ▲ security
- Stability: unverified → 0.03 ▲ functional
- Package version: 0.25.0 → 0.26.0 functional
- 20 Oct 26 61
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 23 Oct 2026 · Analysed pypi/lium.io@0.28.1
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 | Datura-ai/lium |
| Certificate issuer | https://token.actions.githubusercontent.com |
| Certificate SAN | https://github.com/Datura-ai/lium/.github/workflows/publish-pypi.yml@refs/heads/main |
| Rekor log index | 3409076028 |
| Predicate type | PyPI publish attestation https://docs.pypi.org/attestations/publish/v1 |
| Subject digest | sha256:7489cc63ed8a4f28c5a7039037e000bec5b64ce1a59a3ab3de7047dc7994dbc3 |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Dependencies 49 packages
| Packages resolved | 49 |
|---|---|
| Stale | 7 |
| Tree resolution | Partial |
The dependency tree was only partially resolved, so these counts may be incomplete.
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 →
get_balance ~30
Use this when you need to know whether you can afford a rental: returns your Lium balance in USD.
Input schema present but exposes no named parameters.
| Name | Type | Req | Description |
|---|---|---|---|
| result | object | yes | – |
No examples provided.
list_gpus ~127
Use this when you need a GPU: lists Lium nodes for rent, cheapest first, with the executor_id rent_pod takes, tier ("secure", or "spot": cheaper, may be reclaimed), reliability_score (0-100) and rent_price_per_hour_usd (what rent_pod bills per hour for the node's free GPUs). gpu_type filters by model ("H100", "RTX 4090", "B200"); gpu_count by GPUs on the node.
| Name | Type | Req | Description |
|---|---|---|---|
| gpu_count | – | – | – |
| gpu_type | – | – | – |
| limit | integer | – | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | object | yes | – |
No examples provided.
list_pods ~31
Use this when you need your pods: lists them with status, GPU, price per hour and SSH command.
Input schema present but exposes no named parameters.
| Name | Type | Req | Description |
|---|---|---|---|
| result | object | yes | – |
No examples provided.
remove_pod ~53
Use this when you are done with a pod: removes it (by pod id, or a huid or name that matches one pod). Billing stops; anything on its disk is gone.
| Name | Type | Req | Description |
|---|---|---|---|
| pod | string | yes | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | object | yes | – |
No examples provided.
rent_pod ~277
Use this when you have picked a node and want to rent a GPU pod on it: rents it and waits until it is running. executor_id is the executor_id from list_gpus, or the id (or rent_url) that docs.lium.io/mcp search_gpus returns. With dry_run=true it rents nothing and returns a quote: tier, reliability, cost per hour and your balance; show that to the user before renting. This spends money: the pod is billed per second at the node's hourly price until remove_pod. Give it a short unique name. If the result has status "pending", the pod is already rented: do not rent again, poll list_pods or remove_pod its pod_id. If it has status "recovered", nothing new was rented: it lists pods earlier calls rented that you have not used yet. To rent another pod next to those, pass their ids as known_pod_ids. One rent_pod runs at a time: while one is still running, another returns the error rent_in_progress and rents nothing.
| Name | Type | Req | Description |
|---|---|---|---|
| dry_run | boolean | – | – |
| executor_id | string | yes | – |
| known_pod_ids | – | – | – |
| name | string | yes | – |
| template_id | – | – | – |
| timeout_seconds | integer | – | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | object | yes | – |
No examples provided.
run_command ~76
Use this when you want to run something on a pod: runs a shell command on a running pod (by pod id, or a huid or name that matches one pod) and returns exit code, stdout and stderr.
| Name | Type | Req | Description |
|---|---|---|---|
| command | string | yes | – |
| pod | string | yes | – |
| timeout_seconds | integer | – | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | object | yes | – |
No examples provided.
How do I install the Lium GPU Cloud MCP server?
Lium GPU Cloud runs locally as a PyPI package, launched with uvx lium.io. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · lium.io
claude mcp add datura-ai-lium -- uvx lium.io
What is the Lium GPU Cloud MCP server?
Lium GPU Cloud is an MCP server listed in the public MCP registry as io.github.Datura-ai/lium. Rent NVIDIA GPU pods on Lium, run commands on them and remove them, billed per second. This page covers its PyPI package (lium.io).
Is the Lium GPU Cloud MCP server safe to use?
Lium GPU Cloud scores 77 out of 100 on VerifyMCP. 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 Lium GPU Cloud MCP server expose?
Lium GPU Cloud exposes 6 tools: list_gpus, rent_pod, list_pods, run_command, remove_pod, get_balance. Their descriptions and schemas cost roughly 594 tokens of context every time the server is loaded.
Is the Lium GPU Cloud MCP server still maintained?
Lium GPU Cloud is still listed as active in the MCP registry. We last reached this channel on 23 October 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 Lium GPU Cloud MCP server under?
Lium GPU Cloud declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.