Azure Platform Engineering Server

A Model Context Protocol (MCP) server connected to real Azure infrastructure. Deploys a live AKS cluster and provides AI agents with real-time access to cluster health, Azure resources, policy validation, and Terraform analysis.

No simulated data. Every API call hits live Azure services.

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What This Does

This MCP server gives AI agents (Claude Code, GitHub Copilot, etc.) structured access to a real Azure platform:

Tool	Data Source	What It Returns
check_cluster_health	Kubernetes API (live AKS)	Real node status, pod health, events, recommendations
validate_manifest	PyYAML parser	Policy compliance for real YAML manifests
analyze_terraform	HCL analysis	Quality score for Terraform modules
query_azure_resources	Azure Resource Manager API	Real resource groups, AKS clusters, VMs

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Architecture

How It Works

Deployment Pipeline

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Live Proof

This was deployed and tested against a real AKS cluster on Azure for Students.

kubectl get nodes

kubectl get pods (with real CrashLoopBackOff)

MCP Server Test Output (LIVE)

Azure Portal

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Infrastructure

Deployed via Terraform in terraform/main.tf:

Resource	Details
Resource Group	mcp-demo-rg (Sweden Central)
AKS Cluster	aks-platform-demo — Kubernetes 1.32
Node Pool	1x Standard_D2as_v4 (cost-optimised)
Network	Azure CNI + Calico network policy
Monitoring	Log Analytics workspace + OMS agent
Workloads	3 namespaces: product-api, product-web, platform-monitoring

The platform-monitoring namespace includes an intentionally failing pod to demonstrate how the health check tool detects and reports real CrashLoopBackOff incidents.

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Setup

Prerequisites

• Azure subscription (Azure for Students works)
• Azure CLI (az)
• Terraform
• kubectl
• Python 3.10+

Deploy

# 1. Clone
git clone https://github.com/sat0ps/mcp-server-azure-platform.git
cd mcp-server-azure-platform

# 2. Login to Azure
az login

# 3. Deploy infrastructure
cd terraform
terraform init
terraform plan
terraform apply

# 4. Configure kubectl
az aks get-credentials --resource-group mcp-demo-rg --name aks-platform-demo

# 5. Deploy sample workloads
kubectl apply -f workloads.yaml

# 6. Install dependencies
cd ..
pip install -r requirements.txt

# 7. Set subscription ID
export AZURE_SUBSCRIPTION_ID=$(az account show --query id -o tsv)

# 8. Test
python test_tools.py

Tear Down (stop costs)

cd terraform
terraform destroy

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Live Test Output

Platform Engineering MCP Server — Live Test Suite
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Testing against REAL Azure infrastructure

TEST: Initialize
  Server: azure-platform-engineering-mcp v1.0.0
  PASS

TEST: Check Cluster Health (LIVE)
  Source: LIVE — Kubernetes API
  Health Score: 100 (healthy)
  Nodes: 1/1 ready
  Pods: 25 running, 0 pending, 0 failed
  Problem pods:
    - platform-monitoring/failing-service: 6 restarts (CrashLoopBackOff)
  PASS

TEST: Query Azure Resources (LIVE)
  Source: LIVE — Azure Resource Manager API
  AKS Clusters found: 1
    - aks-platform-demo (swedencentral) — K8s 1.32 — Succeeded
      Pool: system — Standard_D2as_v4 x1
  PASS

ALL TESTS PASSED (Live Azure)

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Diagrams

Diagram	What It Shows
Architecture Overview	Full system: agent → MCP → live tools → real Azure
MCP Protocol Flow	Real request flow with CrashLoopBackOff detection
Deployment Pipeline	terraform apply → kubectl → test → destroy
Incident Detection	How MCP found the failing-service pod
Policy Validation	YAML validation gate with real PyYAML parsing
Agent Configuration	How agents.md + skills + instructions work together
Terraform PR Review	AI-driven PR review with quality scoring

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Project Structure

├── mcp_server.py              # MCP server (JSON-RPC 2.0 over stdio)
├── tools/
│   ├── kubernetes_live.py     # Real K8s API health checks
│   ├── compliance_live.py     # Real YAML policy validation
│   ├── terraform_live.py      # Terraform HCL analysis
│   ├── azure_resources.py     # Real Azure Resource Manager queries
│   └── azure_metrics.py       # Azure Monitor metrics (SDK v2 WIP)
├── terraform/
│   ├── main.tf                # AKS + monitoring infrastructure
│   └── workloads.yaml         # Sample K8s deployments
├── .claude/
│   ├── agents.md              # Agent behaviour configuration
│   └── mcp.json               # Claude Code MCP config
├── skills/
│   └── SKILL.md               # Repeatable agent procedures
├── instructions/
│   ├── terraform-standards.md # Terraform quality standards
│   └── kubernetes-standards.md# K8s deployment requirements
├── scripts/
│   └── setup.sh               # Automated deployment script
├── diagrams/                  # Architecture diagrams + live screenshots
├── requirements.txt           # Python dependencies
└── test_tools.py              # Live test suite

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Authentication

Uses DefaultAzureCredential — works with az login, managed identity, and service principals. No credentials stored in the repo.

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Related

• Microsoft Azure MCP Server — Microsoft's official generic Azure MCP server
• Model Context Protocol — MCP specification
• platform-engineering-mcp-server — Simulated version (design-first approach)

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License

MIT