Skip to main content
Glama

corpusAI Cloud Pricing

GPU rental quotes

gpu_quotes
Read-onlyIdempotent

Paid (0.01 USDC per call). Latest rental quotes for one GPU model across neo-clouds, marketplaces and other clouds. One row per quote in each provider's latest daily snapshot: provider, market (ondemand, spot = interruptible, bid = marketplace minimum bid, secure/community = RunPod tiers), GPUs in the quoted unit, USD per GPU-hour, quoted unit price, region where the provider exposes one, and provider-specific detail in extra (marketplace host reliability, VRAM, stock status). Sources: RunPod GraphQL, Vast.ai marketplace (cheapest 64 offers per model, on-demand and bid), DataCrunch, Lambda, Vultr, Linode, Oracle Cloud list prices. Snapshots are taken daily.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gpuYesNormalised GPU model from /gpu/models, e.g. `H100 SXM`, `H200`, `B200`, `A100 SXM 80GB`, `L40S`, `RTX 4090`. Example: H100 SXM
marketNoRestrict to one market (`ondemand`, `spot`, `bid`, `secure`, `community`).
providerNoRestrict to one provider (`runpod`, `vast`, `datacrunch`, `lambda`, `vultr`, `linode`, `oci`).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / gpu / description
      Previous value: -"Normalised GPU model from /gpu/models, e.g. `H100 SXM`, `H200`, `B200`, `A100 SXM 80GB`, `L40S`, `RTX 4090`."New value: +"Normalised GPU model from /gpu/models, e.g. `H100 SXM`, `H200`, `B200`, `A100 SXM 80GB`, `L40S`, `RTX 4090`. Example: H100 SXM"
  2. First observed

TDQS

A4.4/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnly and idempotent annotations, the description discloses the paid nature of the call, the one-row-per-quote structure, market semantics, provider sources, and daily snapshot cadence. This gives an agent a strong behavioral model of what to expect before invoking the tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact yet information-dense. It front-loads the cost and core purpose, then explains the output row structure and sources without repetition or filler. Every sentence contributes useful, non-obvious information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema, the description is remarkably complete: it lists output fields, defines market values, describes provider coverage, notes snapshot timing, and flags the call cost. An agent has enough context to invoke the tool correctly and interpret results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful semantics beyond the schema, especially for the market parameter (spot = interruptible, bid = minimum bid, secure/community = RunPod tiers) and provider sources. This extra context helps an agent choose correct parameter values.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that this tool returns the latest rental quotes for one GPU model across multiple providers, which is a specific verb-resource combination. It is unambiguous about what the tool does, but it does not explicitly differentiate itself from sibling tools such as gpu_snapshot or spot_latest.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives a clear use context: retrieve the latest cross-provider rental quotes for a single normalized GPU model. It also usefully notes that input is limited to one GPU model and that snapshots are daily. However, it does not explicitly state when not to use this tool or name better-suited alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources