"DevOps tools: Docker, Kubernetes, ArgoCD, and Terraform" matching MCP servers:

Enables AI assistants to manage Docker containers and Kubernetes resources through natural language, supporting operations like container management, image building, and pod/deployment/service management.

Exposes Terraform/Terragrunt tooling as Claude Code tools for generating variables.tf and mock outputs automatically from input files.

Enables MCP clients to inspect and operate Kubernetes clusters across multiple contexts, with read-only/read-write/admin access modes and security flags controlling namespaces, contexts, deletes, applies, and exec.

Unified MCP server for DevOps engineers that provides real-time read and write access to Kubernetes, ArgoCD, Prometheus, and PagerDuty from any MCP-compatible AI agent.

The Terraform MCP Server is a Model Context Protocol (MCP) server that integrates seamlessly with Terraform Registry and HCP Terraform APIs, enabling advanced automation and interaction capabilities for Infrastructure as Code (IaC) development.

MCP server for managing Terraform infrastructure as code, enabling initialization, planning, applying, destroying, validating, and showing state of Terraform configurations.

Enables AI assistants to interact with Argo CD applications through natural language, providing tools for cluster, project, application, and resource management via stdio and HTTP transports.

Enables AI assistants to search and retrieve information about Terraform providers and modules from the public Terraform registry, including detailed documentation, version information, and resource specifications.

Wraps the Docker Engine API as MCP tools for container and image management. Reduces token consumption by providing typed tools with default summaries and field selection.

Enables AI assistants to interact with Kubernetes clusters through 50 specialized tools for comprehensive cluster management. Supports both local kubectl and remote SSH-based execution for managing pods, deployments, services, and other Kubernetes resources.

Enables connecting to a Kubernetes cluster to manage resources and troubleshoot workloads with kubectl and Helm operations, including logs, scaling, port forwarding, and non-destructive mode.

Enables inspecting, orchestrating, and troubleshooting Docker Engine and Docker Compose environments through six consolidated high-leverage MCP tools.

Enterprise-grade MCP server for Kubernetes operations, supporting local kubeconfig and AWS EKS authentication, with read, write, and destructive operations protected by multi-layer safety guards.

A powerful and flexible Kubernetes MCP server implementation with support for OpenShift.

Provides read-only access to Kubernetes clusters for AI assistants.

An MCP server that enables AI assistants to interact with Kubernetes clusters by translating natural language into kubectl and Helm operations. It allows users to query, manage, and diagnose Kubernetes resources and cluster states through a seamless integration.

A read-only MCP server that exposes your Docker daemon, allowing AI assistants to list containers, inspect their details, and fetch logs without write access.

Enables Docker container management directly through Claude using the Model Context Protocol. Provides 14 tools for managing containers, images, volumes, and Docker Compose deployments through natural language commands.

Universal Docker MCP server for AI assistants (Cursor, Claude Desktop). Manage Docker containers, execute commands, query databases, and handle environment configurations — all through natural language.

Provides a set of read-only Kubernetes functions via an MCP server, enabling interaction with Kubernetes clusters through agents or coding assistants like GitHub Copilot.

An MCP server that gives AI assistants direct access to Kubernetes clusters for pod management and network debugging (DNS, NetworkPolicy, ingress, service mesh) and correlates Dynatrace observability with OpenTelemetry self-monitoring, which automatically ships traces, metrics, and logs to Dynatrace.

Enables AI coding assistants to control a persistent Chrome browser through DevTools Protocol. Supports web navigation, screenshots, element interaction, mobile testing, console logs, and network debugging in a stable Docker environment.

Enables AI agents to manage Docker containers, images, Compose stacks, health checks, and logs through a unified MCP interface, ensuring containers stay running with self-healing capabilities.

Provides a secure MCP interface to execute commands inside Docker Compose service containers, with real-time output capture and configurable timeouts.

Enables AI assistants to manage Docker containers, deploy stacks, and monitor services across multiple Docker hosts from one centralized location. Supports container lifecycle management, Docker Compose operations, and infrastructure orchestration through natural language commands.

Enables AI assistants like Claude to manage Docker containers, images, and Docker Compose deployments through the Model Context Protocol. Provides secure container lifecycle management, image operations, and multi-host Docker server connections.

Enables AI assistants to inspect and manage Docker environments across one or multiple hosts, including listing containers, retrieving logs and stats, and starting, stopping, restarting, or removing containers, with read-only and secret-redaction safeguards.

Enables AI assistants to manage Docker containers, images, networks, volumes, and Compose services through the Model Context Protocol. It supports system operations, command execution within containers, and integration with Docker Hub and GitHub Container Registry.

Enables secure execution of shell commands and file operations within isolated Docker containers. Provides process management, interactive input handling, and comprehensive file system operations for containerized development environments.

An MCP server that allows managing Docker containers through natural language, enabling users to compose, introspect, and debug containers without running commands themselves.