azure

This MCP server provides an interface to integrate Microsoft Azure services with GenAI applications using the AzureMCPServer. It exposes Azure APIs through an MCP-compatible endpoint, handling authentication, rate limiting, error handling, and asynchronous requests to improve throughput when lending Azure data and actions to GenAI workflows. The server is initialized from the AzureMCPServer class and started with a simple call to start(), making it straightforward to incorporate into orchestrations or tooling that rely on MCP for protocol-pagnostic access to Azure services. To run locally, ensure your environment is prepared to authenticate with Azure (via environment variables or a managed identity) and expose the MCP endpoints your downstream tools expect, then launch the Python module as described in the installation guide. The server supports multiple authentication methods, robust retry logic, and async operation to handle concurrent requests efficiently.

Once running, you can leverage the Azure MCP capabilities to query resources, manage identities, monitor services, and perform common Azure tasks through MCP-compatible commands and endpoints. The library abstracts Azure API calls behind the MCP protocol, so GenAI prompts can request Azure actions without embedding Azure SDK specifics in prompts. Monitor logs and error handling to diagnose request failures and ensure credentials and permissions are configured correctly for the actions you intend to perform.

Prerequisites:

• Python 3.8+ installed on your system
• PIP for Python package installation
• Access to the internet to fetch dependencies

Option A: Install from PyPI

1. Create a virtual environment (recommended) python -m venv venv source venv/bin/activate # On Windows use: venv\Scripts\activate
2. Install the Azure MCP server package from PyPI pip install azure-mcp-server

Option B: Install from source

1. Clone the repository git clone https://github.com/LokiMCPUniverse/azure-mcp-server.git
2. Navigate to the project directory cd azure-mcp-server
3. Install in editable mode pip install -e .

Run the server:

• As a module: python -m azure_mcp
• Ensure required environment variables (see notes) are set before starting

Prerequisites recap:

• Python 3.8+
• pip
• Azure credentials or environment configuration for authentication

Environment and configuration tips:

• The server expects Azure authentication credentials to be available either via environment variables or a configured Azure identity. Common approaches include AZURE_CLIENT_ID, AZURE_TENANT_ID, AZURE_CLIENT_SECRET, or using a managed identity.
• You can provide credentials through a .env file or your hosting environment’s secret management system. If using a .env file, load it before starting the server.
• If you hit authentication or permission errors, verify that the service principal or identity has the necessary Azure RBAC roles for the actions you intend to perform.
• The server supports asynchronous operation and rate limiting to ensure stable performance under load. Tune any relevant rate limit or retry configurations if you customize the server behavior.
• If you plan to run in production, consider containerizing the server and mounting secrets securely, and exposing the MCP endpoints through a gateway or API management layer.