"How to interact with an Azure DevOps repository" matching MCP servers:

Enables MCP-capable clients to inventory and operate Azure resources via the Azure Resource Manager API, including resource groups, tags, and VM power, while enforcing governance controls like scoping, protected groups, location allowlists, delete gating, and confirmation.

Enables AI assistants to interact with local Docker containers, Kubernetes clusters, and system logs using the Model Context Protocol.

An MCP server for interacting with Azure. Contains some common Compute and Networking actions, and extensible to add many more.

Provides tools for interacting with Azure services including Storage, Virtual Machines, and App Service operations.

Enables monitoring and management of Azure resources including Virtual Machines (VMs) and Virtual Machine Scale Sets (VMSS) through a RESTful API with secure Service Principal authentication.

Enables AI-assisted DevOps by exposing scoped, role-based tools to inspect and remediate a Docker app stack, with audit logging and allow-listed commands for safe incident response.

Enables querying local MySQL databases and managing Docker containers (listing, logs) through natural language via the Model Context Protocol.

Enables AI agents to securely manage Linux, Docker, Kubernetes, and SSH infrastructure through MCP with permission control, audit logging, and dangerous command filtering.

Enables Docker container management through natural language conversations, including deployment, health monitoring, dependency resolution, auto-redeployment on file changes, and environment snapshots.

A Model Context Protocol server integrating DevOps tools for GitHub, Docker, and filesystem operations.

An AI-powered containerization assistant that helps you build, scan, and deploy Docker containers through VS Code and other MCP-compatible tools.

Enables comprehensive DevOps infrastructure management through tools for Jenkins, Ansible, Terraform, Kubernetes, and Docker operations. Features a sophisticated memory system for context retention and provides validation, generation, and optimization capabilities across DevOps workflows.

Enables users to query Azure HPC/AI Kubernetes clusters for GPU node information and InfiniBand topology details through kubectl commands. Provides tools to list GPU pool nodes with their status and retrieve network topology labels for high-performance computing workloads.

Enables AI agents to query build/deploy status and request operations on a self-hosted Docker/Compose deployment platform, with Observer and Operator skills and approval-based write actions.

Manages and views virtual machines across multiple cloud providers (AWS, Azure, Alibaba Cloud). Enables AI assistants to list, inspect, and control VMs through a unified MCP interface.

A Model Context Protocol server that provides integration with the Coolify API, enabling DevOps teams to manage Coolify deployments, applications, services, and servers through MCP tools.

An MCP server for the Spot.io API that enables management of AWS and Azure Ocean clusters across multiple accounts. It provides tools for cluster inventory, node management, cost analysis, and scaling operations through natural language.

An MCP server implementation that enables AI assistants to interact with and manage Sakura Cloud infrastructure, including servers, disks, networks, and containerized applications.

A MCP server that enables LLMs to interact with iOS simulators through natural language commands.

Enables spawning ephemeral Linux sandbox containers using Docker and executing commands through an interactive TTY interface. Supports collaborative terminal sessions where both AI clients and humans can simultaneously interact with the same container.