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azure-diagrams — Categories.community

v1.0.0
GitHub

About this Skill

Perfect for Cloud Management Agents needing advanced Azure infrastructure visualization capabilities. sarthakdev.me

gamingopgamingop gamingopgamingop
[0]
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Updated: 3/5/2026

Quality Score

Top 5%
65
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
Cursor IDE Windsurf IDE VS Code IDE
> npx killer-skills add gamingopgamingop/sarthak-skill-forge

Agent Capability Analysis

The azure-diagrams MCP Server by gamingopgamingop is an open-source Categories.community integration for Claude and other AI agents, enabling seamless task automation and capability expansion.

Ideal Agent Persona

Perfect for Cloud Management Agents needing advanced Azure infrastructure visualization capabilities.

Core Value

Empowers agents to generate architecture diagrams from ARM templates, Azure CLI output, or natural language descriptions using JSON and Azure services like Virtual Machines and Storage Accounts.

Capabilities Granted for azure-diagrams MCP Server

Automating Azure infrastructure visualization from ARM templates
Generating diagrams from Azure CLI output for easier resource management
Visualizing Azure resources like VNets and Virtual Machines for improved debugging

! Prerequisites & Limits

  • Requires ARM templates or Azure CLI output
  • Limited to Azure services and infrastructure
  • Needs natural language descriptions for diagram generation
Project
SKILL.md
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package.json
240 B
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SKILL.md
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Azure Diagram Generator

Generates architecture diagrams for Azure infrastructure from ARM templates, Azure CLI output, or natural language descriptions.

When to Use

Activate this skill when:

  • User has ARM (Azure Resource Manager) templates (JSON)
  • User provides Azure CLI output (e.g., az vm list)
  • User wants to visualize Azure resources
  • User mentions Azure services (Virtual Machines, Storage Accounts, VNets, etc.)
  • User asks to "diagram my Azure infrastructure"

How It Works

This skill generates Azure-specific diagrams by parsing Azure resources and calling the Eraser API directly:

  1. Parse Azure Resources: Extract resources from ARM templates, CLI output, or descriptions
  2. Map Azure Relationships: Identify Resource Groups, VNets, subnets, and service connections
  3. Generate Eraser DSL: Create Eraser DSL code from Azure resources
  4. Call Eraser API: Use /api/render/elements with diagramType: "cloud-architecture-diagram"

Instructions

When the user provides Azure infrastructure information:

  1. Parse the Source

    • ARM Templates: Extract resources array, identify types (Microsoft.Compute/virtualMachines, etc.)
    • CLI Output: Parse JSON output from az commands
    • Description: Identify Azure service names and relationships
  2. Identify Azure Components

    • Networking: Virtual Networks (VNets), Subnets, Network Security Groups, Load Balancers
    • Compute: Virtual Machines, Virtual Machine Scale Sets, App Services, Functions
    • Storage: Storage Accounts, Blob Storage, File Shares
    • Databases: SQL Databases, Cosmos DB, Redis Cache
    • Security: Network Security Groups, Azure AD, Key Vault
    • Load Balancing: Application Gateway, Load Balancer, Traffic Manager
    • Other: Service Bus, Event Hubs, API Management
  3. Map Relationships

    • VMs in subnets
    • Subnets in VNets
    • VNets in Resource Groups
    • Storage accounts accessed by VMs
    • Databases accessed by applications
    • Network Security Groups attached to subnets
  4. Generate Eraser DSL Convert Azure resources to Eraser DSL:

    • CRITICAL: Label Formatting Rules
      • Labels MUST be on a single line - NEVER use newlines inside label attributes
      • Keep labels simple and readable - prefer separate labels over concatenating too much metadata
      • Format DSL with proper line breaks (one node/group per line, but labels stay on single lines)
      • If including metadata like CIDR blocks or instance types, include them in the same quoted label string: [label: "VNet 10.0.0.0/16"]

    Example:

    myVNet [label: "VNet 10.0.0.0/16"] {
      subnet1 [label: "Subnet 1"] {
        myVM [icon: azure-vm, label: "Virtual Machine"]
        gateway [icon: azure-app-gateway]
      }
      subnet2 [label: "Subnet 2"] {
        database [icon: azure-sql]
      }
    }
    storage [icon: azure-storage]
    myVNet -> myVM
    myVM -> database
    
  5. Make the HTTP Request

    IMPORTANT: You MUST execute this curl command after generating the DSL. Never stop after generating DSL without making the API call.

    CRITICAL: In the X-Skill-Source header below, you MUST replace the value with your AI agent name:

    • If you are Claude (Anthropic), use: claude
    • If you are running in Cursor, use: cursor
    • If you are ChatGPT (OpenAI), use: chatgpt
    • If you are Gemini (Google), use: gemini
    • Otherwise, use your model/agent name in lowercase
    bash
    1curl -X POST https://app.eraser.io/api/render/elements \ 2 -H "Content-Type: application/json" \ 3 -H "X-Skill-Source: eraser-skill" \ 4 -H "Authorization: Bearer ${ERASER_API_KEY}" \ 5 -d '{ 6 "elements": [{ 7 "type": "diagram", 8 "id": "diagram-1", 9 "code": "<your generated DSL>", 10 "diagramType": "cloud-architecture-diagram" 11 }], 12 "scale": 2, 13 "theme": "${ERASER_THEME:-dark}", 14 "background": true 15 }'
  6. Track Sources During Analysis

    As you analyze files and resources to generate the diagram, track:

    • Internal files: Record each file path you read and what information was extracted (e.g., infra/main.bicep - VNet and subnet definitions)
    • External references: Note any documentation, examples, or URLs consulted (e.g., Azure architecture best practices documentation)
    • Annotations: For each source, note what it contributed to the diagram
  7. Handle the Response

    CRITICAL: Minimal Output Format

    Your response MUST always include these elements with clear headers:

    1. Diagram Preview: Display with a header

      ## Diagram
      ![{Title}]({imageUrl})
      

      Use the ACTUAL imageUrl from the API response.

    2. Editor Link: Display with a header

      ## Open in Eraser
      [Edit this diagram in the Eraser editor]({createEraserFileUrl})
      

      Use the ACTUAL URL from the API response.

    3. Sources section: Brief list of files/resources analyzed (if applicable)

      ## Sources
      - `path/to/file` - What was extracted
      
    4. Diagram Code section: The Eraser DSL in a code block with eraser language tag

      ## Diagram Code
      ```eraser
      {DSL code here}
      
    5. Learn More link: You can learn more about Eraser at https://docs.eraser.io/docs/using-ai-agent-integrations

    Additional content rules:

    • If the user ONLY asked for a diagram, include NOTHING beyond the 5 elements above
    • If the user explicitly asked for more (e.g., "explain the architecture", "suggest improvements"), you may include that additional content
    • Never add unrequested sections like Overview, Security Considerations, Testing, etc.

    The default output should be SHORT. The diagram image speaks for itself.

Azure-Specific Tips

  • Resource Groups: Show Resource Groups as logical containers
  • VNets as Containers: Always show VNets containing subnets and resources
  • Network Security Groups: Include NSG rules and attachments
  • Subscriptions: Note subscription context if provided
  • Data Flow: Show traffic flow (Internet → Application Gateway → VM → SQL Database)
  • Use Azure Icons: Request Azure-specific styling in the description

Example: ARM Template with Multiple Azure Services

User Input

json
1{ 2 "resources": [ 3 { 4 "type": "Microsoft.Resources/resourceGroups", 5 "name": "rg-main" 6 }, 7 { 8 "type": "Microsoft.Network/virtualNetworks", 9 "name": "myVNet", 10 "properties": { 11 "addressSpace": { 12 "addressPrefixes": ["10.0.0.0/16"] 13 }, 14 "subnets": [ 15 { 16 "name": "subnet1", 17 "properties": { 18 "addressPrefix": "10.0.1.0/24" 19 } 20 } 21 ] 22 } 23 }, 24 { 25 "type": "Microsoft.Compute/virtualMachines", 26 "name": "myVM", 27 "properties": { 28 "hardwareProfile": { 29 "vmSize": "Standard_B1s" 30 } 31 } 32 }, 33 { 34 "type": "Microsoft.Web/sites", 35 "name": "myAppService", 36 "properties": { 37 "serverFarmId": "/subscriptions/.../serverfarms/myPlan" 38 } 39 }, 40 { 41 "type": "Microsoft.Storage/storageAccounts", 42 "name": "mystorageaccount" 43 }, 44 { 45 "type": "Microsoft.Sql/servers", 46 "name": "mysqlserver", 47 "properties": { 48 "administratorLogin": "admin" 49 } 50 } 51 ] 52}

Expected Behavior

  1. Parses ARM template:

    • Resource Group: rg-main (container)
    • Networking: VNet with subnet
    • Compute: VM, App Service
    • Storage: Storage Account
    • Database: SQL Server
  2. Generates DSL showing Azure service diversity:

    resource-group [label: "Resource Group rg-main"] {
      myVNet [label: "VNet 10.0.0.0/16"] {
        subnet1 [label: "Subnet 1 10.0.1.0/24"] {
          myVM [icon: azure-vm, label: "VM Standard_B1s"]
        }
      }
      myAppService [icon: azure-app-service, label: "App Service"]
      mystorageaccount [icon: azure-storage, label: "Storage Account"]
      mysqlserver [icon: azure-sql, label: "SQL Server"]
    }
    
    myAppService -> mystorageaccount
    myVM -> mysqlserver
    

    Important: All label text must be on a single line within quotes. Azure-specific: Show Resource Groups as containers, include App Services, Storage Accounts, and SQL databases with proper Azure icons.

  3. Calls /api/render/elements with diagramType: "cloud-architecture-diagram"

Example: Azure CLI Output

User Input

User runs: az vm list --output json
Provides JSON output

Expected Behavior

  1. Parses JSON to extract:

    • VM names, sizes, states
    • Resource groups
    • Network interfaces
    • Storage accounts
  2. Formats and calls API

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