Azure Infrastructure MCP Server

Azure Infrastructure MCP Server

An MCP server for managing Azure infrastructure from AI assistants, supporting subscriptions, VMs, storage, networking, identity, and more through natural language commands.

Category
Visit Server

README

Azure Infrastructure MCP Server

A Model Context Protocol (MCP) server for managing Azure infrastructure directly from AI assistants like Claude in Cursor, VS Code, Claude Desktop, or any MCP-compatible client.

What You Can Do

  • Manage Subscriptions — List and switch between Azure subscriptions
  • Inspect Accounts — View subscription details, get access tokens, clear cached credentials
  • Organize Resources — List and manage resource groups, tags, locks
  • Control VMs — Start, stop, restart, deallocate virtual machines and scale VMSS
  • Manage Storage — List and inspect storage accounts
  • App Configuration — Manage App Configuration stores and key-values
  • App Service — List and manage App Service plans and web apps
  • Deploy Web Apps — Create and manage Web Apps for Containers with Docker/Podman
  • Container Registry — List, create, and manage ACR instances, images, tasks, and network rules
  • Virtual Networks — Create and manage VNets, subnets, and peerings
  • Identity & Access — Manage Azure AD users, groups, applications, and RBAC permissions
  • Governance — Work with management groups, resource locks, and tags
  • Audit — View activity logs and track changes
  • Docker Runtime — List, inspect logs, and restart local Docker containers
  • Monitoring — System metrics, service health, and infrastructure status

Quick Start

1. Prerequisites

  • Python 3.10+
  • Azure CLI installed and logged in (az login)
  • uv package manager (recommended) — or plain pip

2. Install

Option A — Install from PyPI (recommended):

pip install azops-mcp
# or
uv pip install azops-mcp

Option B — Run with uvx (zero-install):

uvx azops-mcp

uvx downloads the package into a cached, isolated environment and runs the server — nothing is installed permanently.

Option C — From source:

git clone https://github.com/artemkozlenkov/azops-mcp.git
cd azops-mcp
./quickstart.sh

3. Configure Your AI Client

Claude Desktop — add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

Important: Claude Desktop does not inherit your shell's PATH. You must use the full absolute path to uvx (or any other command). Find it with which uvx.

Using uvx (recommended — no install required):

{
  "mcpServers": {
    "azops-mcp": {
      "command": "/Users/YOUR_USERNAME/.local/bin/uvx",
      "args": ["azops-mcp"]
    }
  }
}

Using a pip-installed package:

{
  "mcpServers": {
    "azops-mcp": {
      "command": "/Users/YOUR_USERNAME/.local/bin/azops-mcp"
    }
  }
}

Using a local clone (development):

{
  "mcpServers": {
    "azops-mcp": {
      "command": "/Users/YOUR_USERNAME/.local/bin/uv",
      "args": ["--directory", "/full/path/to/azops-mcp", "run", "python", "-m", "azops_mcp"]
    }
  }
}

<details> <summary>Troubleshooting: "Failed to spawn process: No such file or directory"</summary>

This error in ~/Library/Logs/Claude/mcp-server-azops-mcp.log means Claude Desktop cannot find the binary. Claude Desktop only searches system paths (/usr/local/bin, /opt/homebrew/bin, /usr/bin, /bin) — it does not search ~/.local/bin or paths from your shell profile.

Fix: Replace "command": "uvx" with the full path from which uvx (e.g. /Users/yourname/.local/bin/uvx).

</details>

Cursor — add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "azops-mcp": {
      "command": "uvx",
      "args": ["azops-mcp"]
    }
  }
}

Windsurf — add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "azops-mcp": {
      "command": "uvx",
      "args": ["azops-mcp"]
    }
  }
}

VS Code (GitHub Copilot) — add to .vscode/mcp.json in your workspace:

{
  "servers": {
    "azops-mcp": {
      "command": "uvx",
      "args": ["azops-mcp"]
    }
  }
}

Zed — add to your Zed settings file:

{
  "context_servers": {
    "azops-mcp": {
      "command": {
        "path": "uvx",
        "args": ["azops-mcp"]
      }
    }
  }
}

Continue (VS Code / JetBrains) — add to ~/.continue/config.yaml:

mcpServers:
  - name: azops-mcp
    command: uvx
    args:
      - azops-mcp

Note: Cursor, Windsurf, VS Code, and Zed inherit your shell's PATH, so uvx usually works as-is. If not, use the full path from which uvx. See the full docs for details.

To pass environment variables (e.g. Azure credentials), add an "env" key:

{
  "mcpServers": {
    "azops-mcp": {
      "command": "uvx",
      "args": ["azops-mcp"],
      "env": {
        "AZURE_SUBSCRIPTION_ID": "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"
      }
    }
  }
}

Restart your AI client after saving the configuration.

4. Start Using

User: List my Azure subscriptions
User: Show resource groups in subscription xxx-xxx-xxx
User: Start the VM "web-server" in resource group "production"
User: What VMs are running in my dev resource group?

Authentication

Priority Method When
1 Service Principal AZURE_CLIENT_ID + SECRET + TENANT_ID all set in .env
2 Azure CLI After az login (recommended for development)
3 Managed Identity When running in Azure

See the Authentication docs for the full walkthrough.

Available Tools (90+)

Category Tools
Health health_check
Subscriptions & Auth list_subscriptions, set_subscription, auth_status, account_show, account_clear, account_get_access_token, list_locations, list_tenants
Management Groups list_management_groups, get_management_group
RBAC list_role_definitions, create_role_assignment, delete_role_assignment, list_role_assignments_for_principal
Governance list_resource_locks, list_tags, get_activity_log
Resource Groups list_resource_groups, list_resources
VMs & VMSS list_vms, get_vm_status, start_vm, stop_vm, restart_vm, deallocate_vm, scale_vmss
Storage list_storage_accounts, get_storage_status
App Configuration appconfig_list, appconfig_show, appconfig_kv_list, appconfig_kv_show, appconfig_kv_set, appconfig_kv_delete
App Service appservice_plan_list, appservice_plan_show, webapp_list, webapp_show, webapp_start, webapp_stop, webapp_restart
Web Apps for Containers webapp_create_for_container, webapp_grant_cr_access, webapp_configure_vnet_integration, webapp_assign_identity, webapp_view_logs, webapp_set_container_registry_credentials, webapp_delete
Container Registry acr_list_registries, acr_show_registry, acr_create_registry, acr_delete_registry, acr_update_registry, acr_get_credentials, acr_get_login_server, acr_list_repositories, acr_list_tags, acr_show_task, acr_list_tasks, acr_create_task, acr_delete_task, acr_run_task, acr_list_builds, acr_show_quotas, acr_show_usage, acr_list_network_rules, acr_update_network_rules, acr_reset_client
Virtual Networks vnet_list, vnet_show, vnet_create, vnet_delete, vnet_subnet_list, vnet_subnet_show, vnet_subnet_create, vnet_subnet_delete, vnet_peering_list
Azure AD (Entra ID) aad_list_users, aad_show_user, aad_create_user, aad_delete_user, aad_list_applications, aad_create_application, aad_list_groups, aad_verify_tenant, aad_reset_client
Docker Runtime list_containers, get_container_logs, restart_container
Monitoring get_system_metrics, check_service_health, get_infrastructure_status

Docker

Run the MCP server as a container:

# Build the image
docker compose build

# Run the MCP server interactively (stdio transport)
docker compose run --rm mcp-server

See the Docker docs for full instructions.

Project Structure

azops-mcp/
├── src/azops_mcp/
│   ├── __main__.py               # Module entry point
│   ├── server.py                 # MCP server — 93 tool definitions
│   ├── config.py                 # Configuration management
│   ├── tools/                    # Azure SDK integrations (by category)
│   │   ├── _clients.py           # Shared auth & Azure SDK client factories
│   │   ├── subscription.py       # Subscriptions, auth, tenants, locations
│   │   ├── resource_groups.py    # Resource groups, tags, locks, activity log
│   │   ├── compute.py            # VMs, VMSS, resource listing
│   │   ├── networking.py         # VNets, subnets, peerings
│   │   ├── authorization.py      # RBAC roles & assignments
│   │   ├── management_groups.py  # Management group hierarchy
│   │   ├── app_configuration.py  # App Configuration stores & key-values
│   │   ├── app_service.py        # App Service plans & web apps
│   │   ├── container_registry.py # Azure Container Registry (ACR)
│   │   ├── active_directory.py   # Azure AD / Entra ID
│   │   ├── webapp_deployment.py  # Web App for Containers deployment
│   │   ├── docker.py             # Local Docker container runtime
│   │   └── monitoring.py         # System metrics & health
│   └── utils/
│       └── helpers.py            # HTTP client, error formatting
├── tests/                        # Unit tests (per integration)
│   ├── test_subscription.py
│   ├── test_resource_groups.py
│   ├── test_compute.py
│   ├── test_networking.py
│   ├── test_authorization.py
│   ├── test_container_registry.py
│   ├── test_active_directory.py
│   ├── test_webapp_deployment.py
│   ├── test_docker.py
│   ├── test_monitoring.py
│   ├── test_health.py
│   └── test_config.py
├── docs/                          # GitHub Pages documentation
├── Dockerfile                     # MCP server container image
├── docker-compose.yml             # Docker Compose for the MCP server
├── pyproject.toml                 # Dependencies & metadata
├── quickstart.sh                  # Setup script
└── .env.example                   # Configuration template

Configuration

Variable Default Description
AZURE_SUBSCRIPTION_ID Default subscription
AZURE_DEFAULT_LOCATION eastus Default region for new resources
LOG_LEVEL INFO DEBUG, INFO, WARNING, ERROR
RATE_LIMIT_ENABLED true Enable rate limiting
RATE_LIMIT_REQUESTS_PER_MINUTE 60 Max requests/minute

See .env.example for the complete list.

Development

# Install with dev dependencies
uv pip install -e ".[dev]"

# Run tests
pytest

# Code quality
black src/ tests/
ruff check src/ tests/
mypy src/

# Run server manually
uv run python -m azops_mcp

Documentation

Full documentation is available at azops.softawebit.com.

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured