Kubernetes MCP server

Manages self-hosted cloud development environments and AI coding agents using Terraform-defined workspaces.

Enables local development by bulk port forwarding Kubernetes services to your workstation with automatic service name resolution via /etc/hosts.

Enables AI agents to perform step-through debugging, set breakpoints, and inspect variables across ten programming languages using the Debug Adapter Protocol.

Lets an AI client analyze repositories, generate Dockerfiles and Kubernetes manifests, build and scan images, and deploy containers.

Lets an AI assistant inspect, query, and diagnose Octopus Deploy projects, releases, deployments, runbooks, and targets.

Enables an AI client to create, manage, and operate Kubernetes clusters and workloads across local and cloud environments.

Lets AI assistants query and manage Kubernetes clusters by running kubectl commands from natural language requests.

Lets AI assistants run Azure CLI and kubectl commands to manage and diagnose Azure Kubernetes Service clusters.

Runs and manages MCP servers in isolated containers with enterprise-grade security, observability, and Kubernetes integration.

Lets an AI client list and inspect Portainer environments and manage Docker and Kubernetes resources through the Portainer API.

Deploys self-hosted generative AI infrastructure like LLM serving, gateways, and vector databases on Amazon EKS using a CLI.

An SRE agent platform that automates incident investigation and production infrastructure management using multi-agent workflows.

A self-hosted gateway that manages Codex-compatible agents and tools through stable API keys and automatic account routing.

Lets you install, run, and manage MCP servers in secure containers and connect them to AI clients like Cursor and Claude Code.

Acts as a fail-closed execution firewall that quarantines MCP tools, proxies requests, and issues signed receipts for AI agent actions.

Securely execute LLM-generated code in isolated containers or local Linux and Windows sandboxes across multiple programming languages.

Enables AI clients to manage Kubernetes and OpenShift resources through direct API interaction, including pod operations, Helm charts, and Tekton pipelines.

Lets an AI client query cluster-wide Kubernetes network traffic, investigate API calls, and perform root cause analysis using eBPF-powered observability.

Lets an AI client draw and edit draw.io diagrams on a live canvas from chat prompts and exports them as .drawio, .png or .svg files.

Manage test workflows, executions, and artifacts within Kubernetes using AI assistants.

Lets AI assistants list, inspect, create, update, sync, and delete Argo CD applications, clusters, projects, and managed resources.

Enables AI agents to monitor Docker and Kubernetes infrastructure, investigate logs, and manage alerts through a built-in MCP server.

Provides a local-first runtime for AI agents with sandboxed tool execution, persistent sessions, and credential management.

Enables AI agents to perform code-driven diagnostics and analysis of Kubernetes, Helm, Argo, and Argo CD clusters using a sandboxed TypeScript runtime.

Lets an AI client manage Kubernetes clusters by executing kubectl commands, managing Helm charts, and troubleshooting pods.

Lets AI assistants inspect and manage Kubernetes clusters, debug pods, deploy workloads, and audit security via natural language.

Converts existing MCP servers and REST APIs into MCP endpoints through YAML configuration with a built-in management UI.

Enables AI clients to perform intelligent Kubernetes operations, cluster querying, and automated DevOps remediation through natural language.

Lets an AI client inspect Kubernetes clusters for issues, topology, events, changes, logs, Helm, and audits.

Operate self-hosted OpenClaw and Hermes agent fleets on Docker or Kubernetes using natural language through MCP clients.

Enables AI agents to safely operate multi-cluster Kubernetes fleets through Open Cluster Management with policy enforcement and human approval.

Enables AI clients to parse, search, and debug log files across multiple formats using specialized tools for error extraction and sensitive data scanning.

Manage American Cloud infrastructure including VMs, Kubernetes, databases, storage, networking, and DNS through an AI assistant.

Lets an AI client inspect and manage Kubernetes cluster resources, pod logs, metrics, events, and Helm releases.

Enables agentic Kubernetes troubleshooting through natural language diagnosis across multi-cluster fleets.

Inspect and manage IONOS CLOUD infrastructure including Compute, Kubernetes, DNS, and Object Storage through natural-language prompts.

Provides a safe, controlled interface for AI agents to observe, troubleshoot, and perform limited recovery actions within Kubernetes clusters.

Provides a unified observability gateway that normalizes data from multiple backends like Prometheus and Loki for AI agents to perform incident triage.

Turns natural language, code, and infrastructure sources into editable draw.io architecture diagrams, with sync, testing, and export tools.

Run an enterprise AI platform that proxies LLM providers, hosts a private MCP registry, and governs agent tool calls with guardrails.

Inspect Kairon virtual machines, network policies, and VM-edge flows using an agent-based MCP server.

Provides AI agents with real-time read and write access to Kubernetes, ArgoCD, Prometheus, PagerDuty, and Loki infrastructure.

Exposes Talos Linux cluster management to AI agents via structured gRPC tools for managing resources, services, logs, and configuration.

Provides a persistent, isolated agent runtime that lets AI agents build, deploy, and verify code in secure Linux containers via MCP.

Lets AI assistants understand and manage Crossplane control planes by inspecting resources, diagnosing failures, and detecting infrastructure drift.

Lets an AI client query, create, update, and delete Kubernetes resources and manage Helm releases and repositories via kubeconfig.

Enables AI agents to query and reason over real-world attack paths, reachable routes to sensitive assets, and simulated security fixes.

Manages Nife.io cloud applications, sites, secrets, and Git integrations through a GraphQL-powered MCP interface.

Provides a governed control plane for Docker and Kubernetes operations, allowing AI agents to execute scoped, audited, and guardrailed commands.

Allows an AI client to inspect Kubernetes clusters by listing resources, fetching logs, viewing events, and monitoring metrics in a read-only mode.