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Azure Pricing MCP Server

Azure Pricing MCP Server

by msftnadavbh
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

simulate_eviction

Test application resilience by simulating Spot VM eviction with a 30-second notice via Azure Scheduled Events.

Instructions

Simulate eviction of a Spot VM for testing application resilience. Requires Azure authentication with 'Virtual Machine Contributor' role. The VM will receive a 30-second eviction notice via Scheduled Events.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "vm_resource_id": "<vm_resource_id>"
    },
    "name": "simulate_eviction"
  }
}

Input Schema

NameRequiredDescriptionDefault
vm_resource_idYesFull Azure resource ID of the Spot VM (e.g., '/subscriptions/{sub}/resourceGroups/{rg}/providers/Microsoft.Compute/virtualMachines/{vmName}')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.3.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries full burden and discloses critical behavioral traits: it's a simulation (not actual destruction), requires specific Azure authentication, and triggers a 30-second eviction notice via Scheduled Events. However, it doesn't specify rate limits, error conditions, or what happens after the simulation.

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 perfectly front-loaded with purpose, followed by prerequisites and behavioral details in two efficient sentences with zero wasted words, making it immediately understandable.

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?

For a single-parameter simulation tool with no annotations or output schema, the description provides good context about purpose, prerequisites, and behavioral effects. However, it lacks details about response format or post-simulation state, leaving some gaps in completeness.

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 fully documents the single parameter. The description adds no additional parameter semantics beyond what's in the schema, maintaining the baseline score of 3.

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

Purpose5/5

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

The description clearly states the specific action ('simulate eviction'), target resource ('Spot VM'), and purpose ('for testing application resilience'), distinguishing it from sibling tools focused on cost, pricing, or discovery rather than operational testing.

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 explicitly states when to use this tool ('for testing application resilience') and provides prerequisites ('Requires Azure authentication with 'Virtual Machine Contributor' role'), but does not mention when not to use it or name specific alternatives among the sibling tools.

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

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