Este es un servidor de Protocolo de Contexto de Modelo (MCP) que proporciona acceso a consultas de Azure Resource Graph. Permite recuperar información sobre los recursos de Azure en todas las suscripciones mediante consultas de Resource Graph.
Consultar recursos de Azure mediante consultas de Resource Graph
La consulta predeterminada devuelve el ID, el nombre, el tipo y la ubicación del recurso.
Admite consultas de gráficos de recursos personalizados
Utiliza Azure DefaultAzureCredential para la autenticación
Related MCP server: Azure DevOps MCP Server
Node.js instalado
Suscripción a Azure
CLI de Azure instalada e iniciada la sesión, u otras credenciales de Azure configuradas
Puede ejecutar el servidor MCP utilizando Cursor IDE o Visual Studio Code.
Para integrar el servidor MCP con Cursor IDE:
Clone este repositorio en su máquina local (por ejemplo, C:\YOUR_WORKSPACE\azure-resource-graph-mcp-server )
Construir el proyecto:
npm install
npm run buildAbra Configuración del cursor (JSON) y agregue la siguiente configuración:
{
"mcpServers": {
"azure-resource-graph-mcp-server": {
"command": "node",
"args": [
"C:\\YOUR_WORKSPACE\\azure-resource-graph-mcp-server\\build\\index.js"
],
"env": {
"SUBSCRIPTION_ID": "xxxxxx-xx-xx-xx-xxxxxx"
},
}
}
}Nota : asegúrese de actualizar la ruta para que coincida con la ubicación de su repositorio local.
Reinicie Cursor IDE para aplicar los cambios
Para integrar el servidor MCP con Visual Studio Code:
Clona este repositorio en tu máquina local
Construir el proyecto:
npm install
npm run buildAbra la configuración de VS Code (JSON) presionando Ctrl+Shift+P , escriba "Configuración (JSON)" y seleccione "Preferencias: Abrir configuración de usuario (JSON)".
Agregue la siguiente configuración:
{
"mcp": {
"servers": {
"azure-resource-graph": {
"type": "stdio",
"command": "node",
"args": [
"C:\\YOUR_WORKSPACE\\azure-resource-graph-mcp-server\\build\\index.js"
],
"env": {
"SUBSCRIPTION_ID": "xxxxxx-xx-xx-xx-xxxxxx"
},
}
}
}
}Nota : asegúrese de actualizar la ruta para que coincida con la ubicación de su repositorio local.
Guardar el archivo settings.json
Reinicie VS Code para aplicar los cambios
El servidor MCP ahora estará disponible para usar dentro de VS Code con integración de cursor.
El servidor proporciona la siguiente herramienta:
Recupera recursos y sus detalles de Azure Resource Graph.
Parámetros:
subscriptionId (opcional): ID de suscripción de Azure (el valor predeterminado es el ID configurado)
query (opcional): consulta de gráfico de recursos personalizado (predeterminada en "Recursos | ID del proyecto, nombre, tipo, ubicación")
Primero, asegúrese de haber iniciado sesión en la CLI de Azure ejecutando lo siguiente:
az loginEste paso es crucial para el desarrollo local ya que DefaultAzureCredential utilizará automáticamente sus credenciales de la CLI de Azure.
Configure sus variables de entorno:
Copiar .env.example a .env
Actualice AZURE_SUBSCRIPTION_ID en .env con su ID de suscripción real
Otras variables ( AZURE_TENANT_ID , AZURE_CLIENT_ID , AZURE_CLIENT_SECRET ) son opcionales cuando se usa la autenticación de la CLI de Azure
Asegúrese de tener configuradas las credenciales de Azure correctas. El servidor usa DefaultAzureCredential, que admite:
CLI de Azure
Identidad administrada
Credenciales de Visual Studio Code
Variables de entorno
Si utiliza variables de entorno, configure:
ID DE SUSCRIPCIÓN DE AZURE
ID DE INQUILINO DE AZURE
ID DE CLIENTE DE AZURE
SECRETO DEL CLIENTE AZURE
El servidor incluye un manejo robusto de errores para:
Errores de inicialización del cliente de Azure
Errores de ejecución de consultas
Consultas o parámetros no válidos
Para trabajar en este proyecto:
Realizar cambios en el directorio src
Construir usando npm run build
Pruebe sus cambios ejecutando el servidor
Este proyecto está licenciado bajo la Licencia MIT. Consulte el archivo de LICENCIA para más detalles.
Retrieves resources and their details from Azure Resource Graph. Use this tool to search, filter, and analyze Azure resources across subscriptions. It supports Kusto Query Language (KQL) for complex queries to find resources by type, location, tags, or properties. Useful for infrastructure auditing, resource inventory, compliance checking, and understanding your Azure environment's current state.
| Name | Required | Description | Default |
|---|---|---|---|
| subscriptionId | No | Azure subscription ID | |
| query | No | Resource Graph query, defaults to listing all resources |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool retrieves details and supports KQL for queries, but it does not disclose critical behavioral traits such as whether it's read-only or destructive, authentication requirements, rate limits, or pagination behavior. This leaves significant gaps for an agent to understand how to invoke it safely and effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, starting with the core purpose and usage. Each sentence adds value, such as explaining KQL support and use cases, with no redundant information. However, it could be slightly more concise by integrating the use cases more tightly with the main description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of querying Azure resources with KQL and no annotations or output schema, the description is moderately complete. It covers the purpose, usage context, and parameter hints, but it lacks details on behavioral aspects like safety, response format, and error handling, which are important for an agent to use the tool effectively in this context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the schema already documents both parameters (subscriptionId and query) adequately. The description adds some context by mentioning KQL for complex queries and default behavior, but it does not provide additional semantic details beyond what the schema offers, such as query format examples or subscription ID usage nuances.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 ('retrieves', 'search, filter, and analyze') and resources ('Azure resources'), and it distinguishes its scope by mentioning Azure Resource Graph and KQL. It provides concrete use cases like infrastructure auditing and compliance checking, making the purpose highly specific and actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage through phrases like 'Use this tool to search, filter, and analyze' and lists scenarios such as auditing and inventory, but it does not explicitly state when to use this tool versus alternatives or provide exclusions. With no sibling tools, the lack of comparative guidance is less critical, but it still lacks explicit when/when-not instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
query-resourcesScored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap in purpose. The tool 'query-resources' has a clearly defined and singular function, making it impossible for an agent to confuse it with another tool.
Since there is only one tool, naming consistency is inherently perfect. The tool name 'query-resources' follows a clear verb_noun pattern, and there are no other tools to create inconsistency.
A single tool for an Azure Resource Graph server feels thin and under-scoped. While the tool is powerful, typical MCP servers for cloud resource management offer multiple operations (e.g., list, get, filter, aggregate), making one tool insufficient for comprehensive coverage and likely to limit agent workflows.
The tool surface is severely incomplete for the domain of Azure resource management. It only provides a generic query function, missing essential operations like listing resource types, getting specific resources by ID, aggregating metrics, or managing tags, which are common in such systems and necessary for full agent functionality.
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