"Using Azure DevOps for Task Queries and Code Reviews" 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 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 code-mode MCP server for the Unraid 7.2+ GraphQL API that exposes search and execute tools, allowing LLM agents to introspect and call any GraphQL field via sandboxed JavaScript.

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

An MCP server to create secure code sandbox environment for executing code within Docker containers.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

MCP server that integrates with Coolify to let AI assistants manage Coolify instances via a clean toolkit wrapping the official REST API.

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.

Read-only MCP server to list your SkyNode servers and check their status (IP, state, region, expiry). It does not modify or control servers.

Enables headless control of a DOSBox-X guest, including memory reading and patching, framebuffer capture, input injection, and live code tracing without interfering with the host desktop.

Enables running arbitrary JavaScript code in isolated Docker containers with on-demand npm dependency installation, allowing for ephemeral script execution and long-running services with controlled resource limits.