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MCP-Bridge
Developer ToolsAuto-generatedScore: 28

SubscriptionsManagementClient MCP Server

The SubscriptionsManagementClient API, provided by Microsoft as part of the Microsoft.

Quick Start Summary

The SubscriptionsManagementClient MCP server is a Model Context Protocol bridge that connects AI assistants — including Claude Desktop, Cursor, Windsurf, and VS Code Copilot — to the SubscriptionsManagementClient API through natural language. It exposes 2 API endpoints as callable tools, such as Quotas_List, Quotas_Get. 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-azsadmin-quota. This integration is sourced from the auto SubscriptionsManagementClient OpenAPI specification (v2015-11-01) and has a quality score of 28/99 (fair documentation coverage).

2Endpointstools mapped
NoneAuthopen access
28/99Qualityfair
~30 secSetupno auth
View Hosted Config URLClaude Desktop Setup Guide

Server Details

Category
Developer Tools
Authentication
None
Endpoints
2 operations
Transport
STDIO
Spec Version
v2015-11-01
Install Command
npx -y @mcp/azure-com-azsadmin-quota

Environment Variables

SUBSCRIPTIONSMANAGEMENTCLIENT_API_KEY

Example: your_subscriptionsmanagementclient_api_key

Top Endpoints

GET
/subscriptions/{subscriptionId}/providers/Microsoft.Subscriptions.Admin/locations/{location}/quotas

Quotas_List

GET
/subscriptions/{subscriptionId}/providers/Microsoft.Subscriptions.Admin/locations/{location}/quotas/{quota}

Quotas_Get

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📖 Detailed MCP Integration Guide

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

⚡Capabilities & Use Cases
The SubscriptionsManagementClient API, provided by Microsoft as part of the Microsoft.Subscriptions.Admin resource provider, serves as a critical administrative interface for managing and monitoring service quotas within Azure subscriptions. Its core capability revolves around the programmatic retrieval and inspection of resource usage quotas and limits for specific services and locations. Through its two primary endpoints—GET /subscriptions/{subscriptionId}/providers/Microsoft.Subscriptions.Admin/locations/{location}/quotas and GET /subscriptions/{subscriptionId}/providers/Microsoft.Subscriptions.Admin/locations/{location}/quotas/{quota}—the API enables administrators and automated systems to query both a comprehensive list of all applicable quotas for a given subscription and region, and to retrieve detailed information for a single, specific quota resource. This functionality is indispensable in enterprise environments where governance, cost management, and proactive capacity planning are essential. Typical use cases include automated monitoring to trigger alerts before hitting quota limits during scaling operations, generating compliance reports on resource utilization against allocated limits, and providing programmatic data feeds for dashboards that display real-time service availability and capacity across different geographic locations.
🤖AI Agent Value
Exposing the SubscriptionsManagementClient API as tools within an AI coding assistant via the Model Context Protocol (MCP) fundamentally transforms developer interaction with cloud governance tasks. An AI agent, such as one in Claude Desktop or Cursor, gains direct, contextual access to live subscription and quota data without requiring the developer to manually log into portals or construct complex API calls from memory. This integration allows the AI to act as a knowledgeable cloud operations partner. Instead of a developer pausing their coding workflow to check if a deployment region has sufficient quota for a new virtual machine SKU, they can instruct the AI agent to query the current state. The value lies in the seamless embedding of infrastructure awareness directly into the development loop, reducing context switching, minimizing the risk of deployment failures due to quota exhaustion, and enabling the AI to offer informed suggestions based on real-time constraints rather than static documentation.
💬Example Workflows
In practice, a developer can leverage this MCP server to instruct the AI agent with dynamic, natural language commands that translate into precise API actions. For instance, a command like "Check if we have available quota for G-Series VMs in East US for my production subscription" would prompt the AI to execute the appropriate GET request for the specific quota, analyze the response against current usage, and report back with a clear, actionable summary. The AI could be instructed to perform comparative analysis across regions with a prompt such as "Compare the available Azure SQL logical server quotas between West Europe and North Europe," enabling data-driven decisions on where to deploy new services. For ongoing operations, a developer could set up an automated workflow by asking the AI to "Monitor the total core quota for Standard_D-series VMs in my staging subscription and alert me if available capacity drops below 20%." This allows the AI to periodically poll the endpoint and trigger a notification, effectively creating a lightweight, custom monitoring tool without writing dedicated infrastructure-as-code or monitoring scripts.
🛡️Security & Auth
It is critically important to note that while the provided authentication method is listed as "None," this is highly atypical and insecure for an administrative API of this nature. In a real-world implementation, strong authentication using Azure Active Directory (Azure AD) with OAuth 2.0 is mandatory. Developers must configure the MCP server with appropriate service principals or managed identities and adhere strictly to the principle of least privilege. The identity should be granted only the minimal required permissions, such as the Microsoft.Subscriptions.Admin/quotas/read role, scoped to the specific subscriptions and regions under management. Never use a global administrator or co-administrator account for this purpose. All API calls should be made over HTTPS, and the application credentials (client secrets or certificates) must be stored securely using a secrets manager like Azure Key Vault, never hardcoded in configuration files. This security rigor ensures that while the AI assistant gains powerful querying capabilities, the risk of unauthorized access or privilege escalation is mitigated.

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