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Developer ToolsAuto-generatedScore: 28

UsageManagementClient MCP Server

The UsageManagementClient API, provided by Microsoft Commerce, serves as a comprehensive billing and usage data gateway for Microsoft Azure customers.

Quick Start Summary

The UsageManagementClient MCP server is a Model Context Protocol bridge that connects AI assistants — including Claude Desktop, Cursor, Windsurf, and VS Code Copilot — to the UsageManagementClient API through natural language. It exposes 2 API endpoints as callable tools, such as RateCard_Get, UsageAggregates_List. No authentication is required — setup takes approximately 30 seconds. The server uses STDIO transport and can be installed by running npx -y @mcp/azure-com-commerce. This integration is sourced from the auto UsageManagementClient OpenAPI specification (v2015-06-01-preview) and has a quality score of 28/99 (fair documentation coverage).

2Endpointstools mapped
NoneAuthopen access
28/99Qualityfair
~30 secSetupno auth

Server Details

Category
Developer Tools
Authentication
None
Endpoints
2 operations
Transport
STDIO
Spec Version
v2015-06-01-preview
Install Command
npx -y @mcp/azure-com-commerce

Environment Variables

USAGEMANAGEMENTCLIENT_API_KEY

Example: your_usagemanagementclient_api_key

Top Endpoints

GET
/subscriptions/{subscriptionId}/providers/Microsoft.Commerce/RateCard

RateCard_Get

GET
/subscriptions/{subscriptionId}/providers/Microsoft.Commerce/UsageAggregates

UsageAggregates_List

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📖 Detailed MCP Integration Guide

A technical breakdown of capabilities, agent workflows, and security/configuration best practices.

Capabilities & Use Cases
The UsageManagementClient API, provided by Microsoft Commerce, serves as a comprehensive billing and usage data gateway for Microsoft Azure customers. Its core capabilities are centered around transparency and management of cloud expenditure, offering two primary functions: retrieving the detailed pricing model for services (the Rate Card) and fetching aggregated usage data for a specific subscription (Usage Aggregates). The RateCard endpoint delivers a machine-readable list of all metered services, their associated rates, currency, and applicable tiers, while the UsageAggregates endpoint returns the actual consumption records over time, broken down by service, region, and meter. This API is indispensable for enterprise FinOps (Financial Operations) teams, finance departments, and cloud architects who need to perform precise cost analysis, allocate budgets across departments, implement chargeback models, forecast spending, and optimize resource utilization by identifying underused services. It transforms raw billing data into actionable financial intelligence.
🤖AI Agent Value
Exposing the UsageManagementClient as a set of tools via the Model Context Protocol (MCP) for an AI coding assistant unlocks significant automation and insight potential. Instead of a developer manually querying the Azure portal or crafting complex API calls, the AI agent can directly interact with these endpoints to retrieve real-time billing data on demand. This transforms the AI from a code-completion tool into an active participant in cloud financial management. The AI can answer natural language queries like "What is the hourly rate for an A2 v2 virtual machine in the West Europe region?" by calling the RateCard tool, or "Summarize our compute costs for the last 30 days" by invoking the UsageAggregates tool. This integration allows for dynamic, data-driven development and operational decisions to be embedded directly into workflows.
💬Example Workflows
Developers can instruct the AI agent to perform a variety of dynamic tasks that streamline cloud cost management and development planning. For example, an agent could be directed to "Compare the rate card for two different subscription tiers and list the pricing differences for database services" to inform a subscription upgrade decision. It could also "Pull the last week's usage aggregates, identify the top five most expensive meters, and suggest where to set up cost alerts in the Azure portal." During infrastructure-as-code development, a developer might ask, "For the virtual machine specifications in my Terraform template, calculate the estimated monthly cost using the latest rate card." Furthermore, the AI agent could automate reporting by being instructed to "Generate a weekly cost report summarizing usage by resource group and format it as a CSV file." These workflows shift the burden of data gathering and routine analysis from the developer to the AI, freeing focus for architectural and strategic work.
🛡️Security & Auth
While the API definition may indicate "None" for authentication in a simplified specification, practical and secure implementation is critically dependent on proper Azure Active Directory (Azure AD) authentication and authorization. Developers must configure the MCP server with credentials that have the appropriate permissions, typically requiring a service principal or user identity with roles like "Billing Reader" or "Cost Management Reader" at the subscription scope. Security best practices must be strictly followed: apply the principle of least privilege by granting only the read permissions necessary for the intended use case; never hardcode secrets, instead use secure secret management like Azure Key Vault or environment variables; and isolate the MCP server in a controlled environment, ensuring network rules restrict access if applicable. Configuration should also include specifying the target subscription ID(s) as a parameter, allowing the server to be used across multiple subscriptions within a tenant without embedding sensitive identifiers in the tool schema itself.

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