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

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

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

Enables AI assistants to interact with ArgoCD APIs through standardized MCP tools for managing applications, resources, and deployments.

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

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

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.

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

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 AI agents to execute read-only DevOps operations including kubectl, terraform, helm, docker, and AWS cost analysis through natural language.

An implementation of Model Context Protocol (MCP) server for Argo CD.

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.

Connects AI models to the Terraform Registry via MCP, enabling provider lookups, resource usage examples, and module recommendations for streamlined Terraform workflows.

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.

Turns any AI coding agent or MCP client into a governed DevOps engineer by exposing policy-enforced tools for Kubernetes, Docker, Jira, Git/PR, CI/CD, AWS, Terraform, and incident response, with approvals, audit logging, secret redaction, and rollback enforced outside the model.

A read-only MCP server for inspecting and diagnosing HCP Terraform workspaces, runs, and plan summaries from ChatGPT and other MCP clients. It provides tools to list workspaces, inspect runs, and summarize plans without exposing sensitive data.

Enables generating, validating, planning, and applying Terraform configurations to manage infrastructure through natural language.

A FastMCP-based server that provides a natural language interface to Terraform operations, enabling infrastructure management via simple English commands.

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 inspecting and managing Kubernetes clusters through MCP, including listing deployments and pods, retrieving logs and events, and scaling or restarting deployments.

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.

A Model Context Protocol (MCP) server for producing better Terraform through CLI analysis (tflint, checkov, trivy, kics, infracost), best-practice guidance from terraform-best-practices.com, cloud provider recommendations (Azure, AWS, GCP), and Terraform Registry resource and module guidance.

Enables diagnosing Kubernetes clusters without creating or changing cluster objects, with tools to inspect health, workloads, events, storage, RBAC, custom resources, logs, and configuration.

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