Kubernetes MCP Server (FastMCP)

This project provides a Kubernetes MCP (Model Context Protocol) server built using FastMCP and the official Kubernetes Python client. It exposes a wide range of Kubernetes management and inspection tools as MCP tools, making it easy to interact with your Kubernetes or OpenShift cluster programmatically or via GitHub Copilot.

use https://gitingest.com/jlowin/fastmcp download the above and feed it as a context to your copilot chat

prompt to build a mcp server: build a kubernet mcp server with top 30 kubernetes tools using the jlowin-fastmcp-8a5edab282632443.txt file. Make the functions dynamic so that it works for all cases even when the user does not provide a namespace or resource name.

Features

The MCP server exposes the following Kubernetes operations as MCP tools:

• Pod Management: List, describe, and get logs for pods
• Deployment Management: List, scale, and inspect deployments
• Service Management: List and get details of services
• Namespace Management: List, create, and delete namespaces
• Node Management: List and describe nodes
• ConfigMap & Secret Management: List and get ConfigMaps and Secrets
• Persistent Volumes & Claims: List PVs and PVCs, get PVC details
• Job & CronJob Management: List and get jobs and cronjobs
• Ingress Management: List and get ingresses
• DaemonSet, StatefulSet, ReplicaSet Management: List and get details for each
• Event Management: List and get cluster events

All tools support filtering by namespace where applicable.

Prerequisites

• Python 3.x
• fastmcp
• kubernetes Python client
• kubectl (for cluster access)
• Access to a Kubernetes or OpenShift cluster (kubeconfig or in-cluster config)

Installation

1. Install Python dependencies:

   pip install fastmcp kubernetes
   

2. Ensure python and fastmcp are in your system PATH.

3. Install and configure kubectl and connect to your cluster.

4. (Optional) Update your mcp.json to add the MCP server endpoint:

   "kubernetes-local": {
     "name": "Kubernetes MCP Server",
     "url": "http://localhost:8000/mcp/"
   }
   

Usage

1. Start the MCP server:

   python kube_mcp_server.py
   

2. The server will run on http://0.0.0.0:8000/mcp/ by default.

3. You can now interact with your Kubernetes cluster using MCP tools (e.g., via GitHub Copilot or any MCP client).

Example MCP Tools

• list_pods(namespace=None)
• get_pod_logs(pod_name=None, namespace=None)
• describe_pod(pod_name=None, namespace=None)
• list_deployments(namespace=None)
• scale_deployment(deployment_name, replicas, namespace)
• list_services(namespace=None)
• get_service(service_name=None, namespace=None)
• list_namespaces()
• create_namespace(namespace)
• delete_namespace(namespace)
• list_nodes()
• describe_node(node_name=None)
• list_configmaps(namespace=None)
• get_configmap(configmap_name=None, namespace=None)
• list_secrets(namespace=None)
• get_secret(secret_name=None, namespace=None)
• list_persistent_volumes()
• list_persistent_volume_claims(namespace=None)
• get_pvc(pvc_name=None, namespace=None)
• list_jobs(namespace=None)
• get_job(job_name=None, namespace=None)
• list_cronjobs(namespace=None)
• get_cronjob(cronjob_name=None, namespace=None)
• list_ingresses(namespace=None)
• get_ingress(ingress_name=None, namespace=None)
• list_daemonsets(namespace=None)
• get_daemonset(daemonset_name=None, namespace=None)
• list_statefulsets(namespace=None)
• get_statefulset(statefulset_name=None, namespace=None)
• list_events(namespace=None)
• get_event(event_name=None, namespace=None)
• list_replicasets(namespace=None)
• get_replicaset(replicaset_name=None, namespace=None)

Notes

Example prompt:

1. get me the pods running on the vp1099 namespace.
2. scale down all pods in the vp1099 namespace to 1 replica.

• The server will attempt to use your local kubeconfig, or fall back to in-cluster config if running inside a cluster.
• Make sure your kubectl context is set to the desired cluster/namespace.
• You can extend the server by adding more MCP tools using the @mcp.tool decorator.
• Gitingest support: You can use gitingest to ingest and interact with GitHub repositories directly through MCP, enabling advanced code search and automation workflows alongside your Kubernetes operations.

License

MIT License