get_gpu_prices
utilpeek: GPU prices: cheapest H100, A100, L4 per GPU-hour on AWS, Azure, Google Cloud, Akash. Returns cheapest GPU prices per GPU-hour on AWS, Azure and Google Cloud (list prices) and Akash (marketplace bids with GPUs free), by chip, memory, minimum GPUs per cloud machine, region and price ceili...
This record as markdown: /tools/dev-tanod-tanod/get-gpu-prices.md
What get_gpu_prices does on Tanod
AI agents call get_gpu_prices to retrieve information from Tanod without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
chip | object | — | GPU chip, any case, e.g. H100 or A100 80GB. |
limit | integer | — | Rows to return, 1-100. |
pricing | string | — | Price to rank by; any is the lower of the two and also includes Akash marketplace rows (ranked by median bid); on_demand and spot are cloud list prices only. |
regions | object | — | Region names, e.g. us-east-1. |
provider | object | — | AWS, Azure, Google Cloud or Akash (marketplace bids, with GPUs free). |
rent_vs_buy | object | — | Rent-or-buy break-even against the cheapest matching row: monthly cloud cost, monthly ownership cost, break-even month and totals. When min_gpus_per_machine is |
min_gpu_mem_gb | object | — | Minimum GPU memory in GB. |
max_usd_per_gpu_hour | object | — | Ceiling on the ranked price, USD. |
min_gpus_per_machine | object | — | Minimum GPUs in one cloud machine (1-16). Excludes rows without a known machine shape, including Akash marketplace inventory; count_excluded_unknown_machine_sha |
Parameters from the server's own tool schema.
Why get_gpu_prices is rated Low
Even though get_gpu_prices only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Attacks that exploit this kind of access
The rule that runs get_gpu_prices safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Tanod, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For get_gpu_prices, this is the rule to start with:
get_gpu_prices is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Tanod, apply this rule, and every get_gpu_prices call is checked against it from then on.
Questions about get_gpu_prices
utilpeek: GPU prices: cheapest H100, A100, L4 per GPU-hour on AWS, Azure, Google Cloud, Akash. Returns cheapest GPU prices per GPU-hour on AWS, Azure and Google Cloud (list prices) and Akash (marketplace bids with GPUs free), by chip, memory, minimum GPUs per cloud machine, region and price ceiling; returns USD per machine-hour or null for unknown shape and an unknown-shape exclusion count; optionally rent-or-buy break-even. Input: all optional: chip, min_gpu_mem_gb, min_gpus_per_machine, provider, regions, pricing, max_usd_per_gpu_hour, limit, rent_vs_buy. List prices from a snapshot refreshed twice a day, excluding tax, egress and storage; spot changes often. A snapshot over 36 hours old is a 503 (not charged). Typically under 0.1 s. Price: USD 0.002. Free: 10 utilpeek calls per IP per UTC day. Docs: https://tanod.dev/learn/cloud-gpu-price-api.html. It is categorised as a Read tool in the Tanod MCP Server, which means it retrieves data without modifying state.
get_gpu_prices accepts 9 parameters: chip, limit, pricing, regions, provider, rent_vs_buy, min_gpu_mem_gb, max_usd_per_gpu_hour, min_gpus_per_machine. The full parameter table on this page comes from the server's own tool schema.
Register the Tanod MCP server in PolicyLayer and add a rule for get_gpu_prices: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Tanod. Nothing to install.
get_gpu_prices is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_gpu_prices rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for get_gpu_prices. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
get_gpu_prices is provided by the Tanod MCP server (https://tanod.dev/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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