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Azure Pricing MCP Server

Azure Pricing MCP Server

by msftnadavbh
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

azure_region_recommend

Find cost-effective Azure regions by comparing prices across all available locations for specific services and SKUs, providing ranked recommendations with potential savings.

Instructions

Find the cheapest Azure regions for a given service and SKU. Dynamically discovers all available regions, compares prices, and returns ranked recommendations with savings percentages.

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": {
      "service_name": "<service_name>",
      "sku_name": "<sku_name>"
    },
    "name": "azure_region_recommend"
  }
}

Input Schema

NameRequiredDescriptionDefault
service_nameYesAzure service name (e.g., 'Virtual Machines', 'Azure App Service')
sku_nameYesSKU name to price across regions (e.g., 'D4s v3', 'P1v3')
top_nNoNumber of top recommendations to return (default: 10)
currency_codeNoCurrency code (default: USD)USD
discount_percentageNoDiscount percentage to apply to prices (e.g., 10 for 10% discount). If not specified and show_with_discount is false, no discount is applied. If show_with_discount is true, defaults to 10%.
show_with_discountNoSet to true to apply a discount; uses default 10% unless discount_percentage is explicitly specified.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.3.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions dynamic discovery and savings percentages, but lacks critical details: whether this requires authentication, rate limits, freshness of price data, whether it makes external API calls, or what format the ranked recommendations take. For a tool with 6 parameters and no annotation coverage, this is insufficient.

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

Conciseness4/5

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

The description is a single, well-structured sentence that efficiently communicates the core functionality. It's appropriately sized for the tool's complexity, though it could potentially be more front-loaded by explicitly stating it's a price optimization tool earlier in the sentence.

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

Completeness2/5

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

For a tool with 6 parameters, no annotations, and no output schema, the description is incomplete. It doesn't address authentication requirements, data freshness, error conditions, or the structure of returned recommendations. The agent would need to guess about critical behavioral aspects when invoking this tool.

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 all 6 parameters thoroughly. The description adds minimal value beyond the schema - it implies the tool uses these parameters for region comparison but doesn't provide additional context about parameter interactions or edge cases. Baseline 3 is appropriate when schema does the heavy lifting.

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 tool's purpose with specific verbs ('find', 'discovers', 'compares', 'returns') and resources ('cheapest Azure regions', 'service and SKU'). It distinguishes from siblings by focusing on region-based price comparison rather than general cost estimation or SKU discovery.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus its 11 siblings. While it mentions dynamic discovery and ranked recommendations, it doesn't specify scenarios where this is preferable to alternatives like azure_price_compare or azure_price_search, nor does it mention prerequisites or exclusions.

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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