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azure-vm-pricing-mcp

Estimate Azure VM cost

estimate_vm_cost
Read-only

Estimate monthly and yearly Azure VM costs for one to five sizes, including pay-as-you-go, reservations, savings plans, and break-even hours by region.

Instructions

Monthly and yearly cost of one or more Azure VM sizes for pay as you go, reservations and savings plans, with the break-even hours per month for each commitment. Use it to compare sizes or regions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
osNoOperating system for pay-as-you-go prices. Default linux.
sizesYesOne to five VM sizes to price, e.g. ["Standard_D4s_v5", "Standard_D4as_v6"].
regionNoAzure region, e.g. westeurope or "West Europe". Omit to use each size's cheapest region.
instancesNoNumber of VMs. Default 1.
hours_per_monthNoRuntime hours per month. Default 730 (always on).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations only declare readOnlyHint and openWorldHint, so the description adds real value by disclosing the shape of the result: monthly and yearly figures, three commitment models, and break-even hours per commitment. It doesn't mention rate limits, caching, or pricing-freshness caveats, which keeps it short of a 5.

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?

Two sentences, zero filler, with the output contract front-loaded and the usage hint trailing. Every clause carries information.

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

Completeness4/5

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

With no output schema, the description correctly compensates by summarizing what is returned (monthly/yearly costs, break-even hours). Combined with the fully documented input schema and read-only annotation, an agent has enough to call it correctly; only the pricing-freshness/commitment-selection nuance is left unstated.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents os, sizes, region, instances and hours_per_month with defaults and bounds. The description's mention of commitment types is framing rather than parameter guidance, so baseline 3 applies.

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 names a specific resource (Azure VM sizes) and a specific output (monthly/yearly cost across pay-as-you-go, reservations and savings plans, plus break-even hours). It is clearly distinct from the size-lookup siblings, though it never names them explicitly.

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

Usage Guidelines3/5

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

"Use it to compare sizes or regions" gives an implied use case, but there is no statement of when NOT to use it, no prerequisites, and no pointer to alternatives such as get_price_changes or find_vm_sizes. Adequate but thin.

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