AI Agent for MCP Server Kubernetes
Seamlessly connect and manage your Kubernetes clusters using the MCP Server Kubernetes integration. Automate kubectl operations, scale deployments, manage Helm charts, and securely troubleshoot your Kubernetes resources—all with unified access and advanced security controls. Boost productivity with robust automation and intelligent Kubernetes workflows.
Unified Kubernetes Management
Control your Kubernetes clusters with an all-in-one interface. MCP Server Kubernetes lets you perform essential kubectl operations, manage resources, and switch contexts effortlessly. Streamline your DevOps workflow with automated deployments, resource scaling, and contextual management—without leaving your preferred environment.
- Comprehensive kubectl API.
- Automate get, describe, create, apply, delete, logs, patch, rollout, and generic kubectl commands from a single interface.
- Context Switching.
- Easily switch between multiple Kubernetes contexts for seamless multi-cluster management.
- Resource Scaling.
- Instantly scale deployments and resources to match your workload requirements.
- Secrets Masking.
- Protect sensitive data with built-in secrets masking for kubectl secret operations.
Advanced Automation & Helm Integration
Automate Helm operations, including installing, upgrading, and uninstalling charts with custom values, repositories, and versions. Port forward to pods and services, and leverage advanced troubleshooting prompts for diagnosing issues—all while maintaining non-destructive, secure workflows.
- Helm Chart Management.
- Install, upgrade, and uninstall Helm charts with ease for rapid application delivery.
- Non-Destructive Operations.
- Enable read and create/update-only access to clusters for enhanced safety and compliance.
- Troubleshooting Prompts.
- Leverage AI-powered prompts for systematic diagnosis and remediation of Kubernetes pod issues.
Security, Connectivity & Local Development
Benefit from robust security controls with secrets masking and non-destructive modes. Effortlessly port-forward connections, manage API resources, and enjoy seamless integration with local development tools like Bun, Inspector, and mcp-chat for full-cycle Kubernetes automation and testing.
- Secrets Masking.
- Automatically mask sensitive data in secrets for secure command outputs.
- Port Forwarding.
- Set up and manage port forwarding to pods and services directly from the interface.
- Local Development Ready.
- Supports modern dev workflows with Bun, Inspector, and mcp-chat integration.
MCP INTEGRATION
Available Kubernetes MCP Integration Tools
The following tools are available as part of the Kubernetes MCP integration:
- kubectl_get
List or retrieve Kubernetes resources such as pods, deployments, services, and more.
- kubectl_describe
Display detailed descriptions and status information of a specific Kubernetes resource.
- kubectl_create
Create new Kubernetes resources by providing manifest files or resource specifications.
- kubectl_apply
Apply YAML or JSON manifests to create or update Kubernetes resources declaratively.
- kubectl_delete
Delete Kubernetes resources such as pods, deployments, or namespaces.
- kubectl_logs
Fetch and display logs for one or more Kubernetes pods or containers.
- kubectl_context
Manage or switch between multiple Kubernetes contexts for different clusters.
- explain_resource
Explain the schema and fields of any Kubernetes resource type.
- list_api_resources
List all available Kubernetes API resources and their supported operations.
- kubectl_patch
Update fields of existing Kubernetes resources using patch operations.
- kubectl_scale
Scale deployments or other scalable resources to a desired number of replicas.
- kubectl_rollout
Manage the rollout and status of deployments, including pause, resume, or undo.
- kubectl_generic
Execute any supported kubectl command by specifying the full command and arguments.
- install_helm_chart
Install Helm charts to deploy applications or services onto your Kubernetes cluster.
- upgrade_helm_chart
Upgrade existing Helm releases with new charts, versions, or values.
- uninstall_helm_chart
Uninstall Helm releases and remove all associated Kubernetes resources.
- port_forward
Set up port forwarding from your local machine to Kubernetes pods or services.
- stop_port_forward
Stop active port-forwarding sessions to Kubernetes pods or services.
- k8s-diagnose
Troubleshoot Kubernetes pods by guiding users through systematic diagnostic flows.
- ping
Verify server connectivity and test access to your Kubernetes cluster.
Manage Kubernetes with MCP Server
Effortlessly connect, control, and troubleshoot your Kubernetes clusters with MCP Server Kubernetes. Try it live, or book a personalized demo to see how it can streamline your operations.
What is MCP Server Kubernetes
MCP Server Kubernetes, developed by Flux159, is an advanced server implementation designed to connect to and manage Kubernetes clusters via the Model Context Protocol (MCP). This server acts as a robust bridge, enabling programmatic access to Kubernetes environments for AI agents, automation scripts, or other systems. It supports loading kubeconfig from multiple sources in a prioritized order, ensuring seamless and secure cluster management. By leveraging MCP, the server abstracts and standardizes interactions with Kubernetes, making it easier to automate complex workflows, deploy applications, monitor resources, and maintain infrastructure at scale.
Capabilities
What we can do with MCP Server Kubernetes
With MCP Server Kubernetes, users can automate, monitor, and manage Kubernetes clusters programmatically. The server unlocks a range of features to improve cluster operations, enhance automation, and facilitate seamless integration with AI-driven workflows.
- Cluster Management
- Connect to and manage multiple Kubernetes clusters securely and efficiently.
- Automated Deployments
- Programmatically deploy, update, and rollback workloads or applications.
- Resource Monitoring
- Monitor cluster resources such as pods, nodes, and services in real-time.
- Access Control
- Manage user permissions and configure security policies across clusters.
- Workflow Automation
- Integrate with other AI agents or tools to automate complex, multi-step operations.
What is MCP Server Kubernetes
AI agents can significantly benefit from MCP Server Kubernetes by gaining programmatic, standardized access to Kubernetes clusters. This allows them to autonomously deploy applications, monitor system health, react to changes, and optimize resource utilization. The MCP protocol ensures consistent interactions, making it easier to build intelligent, automated DevOps pipelines and resilient infrastructures.