"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.

Provides Docker management tools for AI agents, including inspecting containers, images, Dockerfiles, and Compose configurations.

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

An MCP (Model Context Protocol) server that integrates with the ArgoCD API, enabling AI assistants and large language models to manage ArgoCD applications and resources through natural language interactions.

A Model Context Protocol (MCP) server for integrating ArgoCD GitOps continuous delivery tool with GenAI applications, enabling intelligent Kubernetes deployment management.

Safety-first GitOps operations for ArgoCD via the Model Context Protocol. Enables listing, diagnosing, syncing, and managing ArgoCD applications with progressive disclosure and defense-in-depth security.

An MCP server designed to retrieve DevOps skills, code standards, and SAP Fiori documentation templates from a GitHub repository. It allows users to list available resources and fetch specific best practices to integrate directly into their development workflow.

Enables AI assistants to interact with Argo CD through its REST API, providing tools to triage application status, sync, roll back, inspect drift, read logs, and manage ApplicationSets, clusters, projects, and repositories. Supports read-only safeguards, curated GitOps resources, and workflow prompts for safe operations.

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.

Enables management of Terraform infrastructure as code through 25 comprehensive tools for operations including plan/apply/destroy, state management, workspace management, and configuration file editing.

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.

An MCP server that wraps terraform-ls to provide Terraform language intelligence as MCP tools, enabling AI assistants to understand and navigate Terraform codebases.

Enables state-aware Terraform/OpenTofu plan evaluation against live AWS topology and CloudWatch telemetry, detecting reliability blast radius and FinOps waste before merge.

Provides hybrid (BM25 + vector) search over Terraform AWS and Google provider documentation, with tools for ranked search and full document retrieval.

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

An MCP server that exposes Terraform CLI operations as tools for Claude and other MCP-compatible AI assistants, enabling AI-driven infrastructure-as-code workflows including planning, applying, and validating 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 interact with ArgoCD APIs through standardized MCP tools for managing applications, resources, and deployments.

An advisory and generative copilot for Terraform that reviews existing scripts and generates compliant infrastructure using organization-specific rules.

MCP server that gives AI assistants full access to Kubernetes clusters and Helm, exposing 73 tools for managing pods, deployments, services, configs, secrets, logs, exec, port-forwarding, Helm lifecycle, and more.

Enables AI agents to manage Terraform modules by searching, inspecting, and scaffolding configurations from private GitHub repositories. Also provides backend S3 configuration for generated Terraform code.

A Model Context Protocol (MCP) server that lets Claude manage Terraform infrastructure through natural language.

Enables coding agents to answer from what is actually true in the current Terraform working directory: the provider schemas pinned in the lock file, saved plans, redacted state, and local or installed module interfaces. It also reports what a pinned provider upgrade would break, all read-only and without ever running init in the root module.

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.

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.

Provides structured DevOps practices and templates (tracking, documentation, runbooks) to streamline AI-assisted PoC development, reducing CLAUDE.md bloat and ensuring consistency across projects.

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.

A Model Context Protocol (MCP) server that integrates Claude with the Terraform Cloud API, allowing Claude to manage your Terraform infrastructure through natural conversation.

Manages Kubernetes clusters through kubectl and Helm operations including pod cleanup, node management, and troubleshooting.

MCP server for Argo CD that provides multi-environment profiles, SSO or API key authentication, application search with cache, and REST API tools from the bundled OpenAPI catalog.