Database
azure-resource-caching - Claude MCP Skill
Feature: Azure Resource Caching System
SEO Guide: Enhance your AI agent with the azure-resource-caching tool. This Model Context Protocol (MCP) server allows Claude Desktop and other LLMs to feature: azure resource caching system... Download and configure this skill to unlock new capabilities for your AI workflow.
Documentation
SKILL.md# Feature: Azure Resource Caching System ## Description This feature implements a comprehensive in-memory caching system for Azure resources that significantly improves performance by reducing Azure API calls and providing faster response times for frequently accessed resources. The caching system is integrated into the Azure client and provides automatic cache management with configurable expiration times. ## How it Works The caching system intercepts Azure SDK calls and stores resource information in memory with time-based expiration. When a resource is requested, the system first checks the cache before making an API call to Azure. This reduces latency, minimizes Azure API rate limiting, and improves overall server performance. ## Architecture ### Core Components - **Azure Cache** - Generic in-memory cache implementation with time-based expiration - **Azure Client Integration** - Cache integration with Azure SDK clients for transparent caching - **Configuration Management** - Configurable cache timeout and expiration settings - **Thread Safety** - Concurrent access protection with read-write mutexes - **Automatic Expiration** - Time-based cache invalidation and cleanup ## Cached Resource Types ### Azure Kubernetes Service Resources - **AKS Clusters**: Complete cluster configuration and status - **Node Pools**: Node pool details and configuration - **Cluster Credentials**: Authentication and access information ### Networking Resources - **Virtual Networks (VNets)**: VNet configuration and address spaces - **Subnets**: Subnet details and IP allocations - **Network Security Groups (NSGs)**: Security rules and associations - **Route Tables**: Routing configuration and rules - **Load Balancers**: Load balancer configuration and backend pools ### Resource Metadata - **Resource Hierarchies**: Parent-child relationships between resources - **Resource IDs**: Azure resource identifiers and references - **Resource States**: Current operational state of resources ## Cache Key Strategy ### Hierarchical Key Structure Cache keys follow a structured pattern for easy management and retrieval: ``` Format: resource:type:subscription:resourcegroup:name Examples: - "resource:cluster:12345678-1234-1234-1234-123456789012:myRG:myCluster" - "resource:vnet:12345678-1234-1234-1234-123456789012:networkRG:myVNet" - "resource:nsg:12345678-1234-1234-1234-123456789012:aksRG:myNSG" - "resource:routetable:12345678-1234-1234-1234-123456789012:aksRG:myRT" ``` ### Key Benefits - **Predictable Structure**: Easy to construct and understand - **Collision Avoidance**: Unique keys across all Azure subscriptions - **Scope Isolation**: Resources isolated by subscription and resource group - **Type Organization**: Clear resource type identification
Signals
Information
- Repository
- Azure/aks-mcp
- Author
- Azure
- Last Sync
- 3/13/2026
- Repo Updated
- 3/11/2026
- Created
- 1/16/2026
Reviews (0)
No reviews yet. Be the first to review this skill!
Related Skills
mem0
Integrate Mem0 Platform into AI applications for persistent memory, personalization, and semantic search. Use this skill when the user mentions "mem0", "memory layer", "remember user preferences", "persistent context", "personalization", or needs to add long-term memory to chatbots, agents, or AI apps. Covers Python and TypeScript SDKs, framework integrations (LangChain, CrewAI, Vercel AI SDK, OpenAI Agents SDK, Pipecat), and the full Platform API. Use even when the user doesn't explicitly say "mem0" but describes needing conversation memory, user context retention, or knowledge retrieval across sessions.
upgrade-nodejs
Upgrading Bun's Self-Reported Node.js Version
cursorrules
CrewAI Development Rules
cn-check
Install and run the Continue CLI (`cn`) to execute AI agent checks on local code changes. Use when asked to "run checks", "lint with AI", "review my changes with cn", or set up Continue CI locally.
Related Guides
Bear Notes Claude Skill: Your AI-Powered Note-Taking Assistant
Learn how to use the bear-notes Claude skill. Complete guide with installation instructions and examples.
Mastering tmux with Claude: A Complete Guide to the tmux Claude Skill
Learn how to use the tmux Claude skill. Complete guide with installation instructions and examples.
OpenAI Whisper API Claude Skill: Complete Guide to AI-Powered Audio Transcription
Learn how to use the openai-whisper-api Claude skill. Complete guide with installation instructions and examples.