We’re excited to announce improved Python support for the Azure Model Context Protocol (MCP) Server! Python developers can now install and run Azure MCP Server directly from PyPI using familiar tools like uvx and pip. Whether you’re building agentic workflows, automating Azure resources, or experimenting with AI-powered development, getting started with Azure MCP Server in Python has never been easier.

Why Python support matters

Python is one of the most popular languages in the AI and data science ecosystem. Many developers building AI agents, automation scripts, and intelligent applications rely on Python as their primary language. Until now, using the Azure MCP Server required either Node.js (npm/npx) or .NET (dnx) as a runtime. With the new PyPI package, Python developers can stay in their preferred ecosystem while getting full access to the Azure MCP Server’s 40+ Azure service integrations.

Get started with Python

Run directly with uvx (recommended)

The fastest way to get started is with uvx, which runs the Azure MCP Server without requiring a permanent installation:

uvx --from msmcp-azure azmcp server start

This command downloads and runs the latest version on demand, so you always get the newest features and fixes.

Install with pip

For integration into an existing Python project or virtual environment:

pip install msmcp-azure

You can also pin a specific version:

pip install msmcp-azure==<version>

Prerequisites

• uv for uvx commands
• Python 3.10+ for pip installation

Configure your MCP client for Python

Once installed, configure your IDE or MCP client to use the Python-based server. Add the following to your mcp.json:

{
  "mcpServers": {
    "azure-mcp-server": {
      "command": "uvx",
      "args": [
        "--from",
        "msmcp-azure",
        "azmcp",
        "server",
        "start"
      ]
    }
  }
}

This configuration works across Visual Studio (VS) Code, Visual Studio, IntelliJ, Eclipse, Claude Desktop, Cursor, and any other MCP-compatible client. For IDE-specific file locations, see the Azure MCP Server documentation.

Note: Remember to authenticate to Azure before running the server. See the Authentication guide for details.

When to use uvx vs. pip

Use the GitHub Copilot SDK with Python

The new Python package also works seamlessly with the GitHub Copilot SDK. Here’s a quick example of how to configure an agentic session with Azure MCP tools:

import asyncio
from copilot import CopilotClient

async def main():
    client = CopilotClient()
    await client.start()

    session = await client.create_session(
        session_config={
            "mcp_servers": {
                "azure-mcp": {
                    "command": "uvx",
                    "args": ["--from", "msmcp-azure", "azmcp", "server", "start"],
                    "tools": ["*"]
                }
            }
        }
    )

    response = await session.send_message(
        "List my Azure Storage containers"
    )
    print(response.text)

    await client.stop()

if __name__ == "__main__":
    asyncio.run(main())

What you can do with Azure MCP Server

With this update, Python developers have the same access as Node.js and .NET users to the full set of Azure MCP Server capabilities, including:

• 40+ Azure services—from Microsoft Foundry and AI Search to Cosmos DB, Storage, Key Vault, and more
• IDE integrations—VS Code, Visual Studio, IntelliJ, Eclipse, and beyond
• Flexible server modes—namespace (default), all, or single tool modes
• Read-only mode—prevent write operations for safer exploration
• Docker support—run as a container in CI/CD pipelines

Try prompts like:

• “List my Azure Storage containers”
• “Show me my Cosmos DB databases”
• “What indexes do I have in my Azure AI Search service?”
• “Generate Azure CLI commands to create a new resource group”

Get started today

• PyPI Package: msmcp-azure
• GitHub Repo: aka.ms/azmcp
• Documentation: aka.ms/azmcp/docs
• VS Code Extension: aka.ms/azmcp/download/vscode
• Create an Issue: aka.ms/azmcp/issues

Summary

Azure MCP Server now has first-class Python support via PyPI. Install with uvx or pip and connect your AI agents to over 40 Azure services in seconds. Whether you’re building in VS Code, running in a CI pipeline, or scripting automation, the Python package gives you a native, lightweight path to agentic Azure development. Try it out and let us know what you think!