3 posts tagged with "MCP"

It's been a few months since the AKS-MCP server was announced. Since then, there have been several updates and improvements. The MCP server can be easily installed on a local machine using the AKS Extension for VS Code, or via the GitHub MCP registry, or even using the Docker MCP hub.

In this blog post, I'll show you one approach to running the AKS MCP server: deploying it inside an AKS cluster as a Streamable HTTP service. This pattern demonstrates how MCP servers can be centrally managed and made accessible to multiple clients—including AI assistants, automation tools, and even autonomous agents.

Introduction​

Recently, we released the AKS-MCP server, which enables AKS customers to automate diagnostics, troubleshooting, and cluster management using natural language. One of its key capabilities is real-time observability using inspektor_gadget_observability MCP tool, which leverages a technology called eBPF to help customers quickly inspect and debug applications running in AKS clusters.

We're excited to announce the launch of the AKS-MCP Server. An open source Model Context Protocol (MCP) server designed to make your Azure Kubernetes Service (AKS) clusters AI-native and more accessible for developers, SREs, and platform engineers through Agentic AI workflows.

AKS-MCP isn't just another integration layer. It empowers cutting-edge AI assistants (such as Claude, Cursor, and GitHub Copilot) to interact with AKS through a secure, standards-based protocol—opening new possibilities for automation, observability, and collaborative cloud operations.