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K8scortex MCP

by apatilgtnversion 1.1.3i★ –iRuns on your computer
Registry nameio.github.apatilgtn/k8scortex-mcp

Install

Overview

Description from the maker (original English)

Kubernetes MCP server: 75 tools for GKE, AKS, EKS, RBAC, audit logging, GitOps, multi-cluster.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Developer tools

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: KUBECONFIG, CLUSTERS_CONFIG, K8SCORTEX_STDIO_ROLES

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "k8scortex": {
      "command": "npx",
      "args": [
        "-y",
        "k8scortex-mcp"
      ],
      "env": {
        "KUBECONFIG": "your-value",
        "CLUSTERS_CONFIG": "your-value",
        "K8SCORTEX_STDIO_ROLES": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add k8scortex --env KUBECONFIG=your-value --env CLUSTERS_CONFIG=your-value --env K8SCORTEX_STDIO_ROLES=your-value -- npx -y k8scortex-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "k8scortex": {
      "command": "npx",
      "args": [
        "-y",
        "k8scortex-mcp"
      ],
      "env": {
        "KUBECONFIG": "your-value",
        "CLUSTERS_CONFIG": "your-value",
        "K8SCORTEX_STDIO_ROLES": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "k8scortex": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "k8scortex-mcp"
      ],
      "env": {
        "KUBECONFIG": "your-value",
        "CLUSTERS_CONFIG": "your-value",
        "K8SCORTEX_STDIO_ROLES": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • KUBECONFIG env
    Path to your kubeconfig file. Each context becomes a cluster. Defaults to ~/.kube/config.
  • CLUSTERS_CONFIG env
    Optional path to a cluster registry JSON file mixing kubeconfig, EKS, GKE and Key Vault clusters.
  • K8SCORTEX_STDIO_ROLES env
    Roles for the local session, e.g. 'developer' for read-only tools. Defaults to platform-engineer.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account apatilgtn, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Developer toolsi

  • More stars than 0% of the other 4907 servers in this category
  • Published to the registry more recently than 76% of the other 4907 servers in this category
  • Basic checks equal to or better than 100% of the other 4907 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is K8scortex MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.1.3) reached the registry 12 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js, Docker on your computer.

What can I use instead?

In the same category: GitHub, Desktop Commander, Cloudflare MCP

Alternatives

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

K8sCortex — Kubernetes MCP Server

Give your AI agents Kubernetes access your security team will sign off on. K8sCortex is one governed MCP gateway for GKE, EKS, AKS, OpenShift and local clusters: SSO on every request, role tiers, per-cluster policies, dry-run by default, and an audit log of who asked for what.

Most Kubernetes MCP servers hand an agent your kubeconfig. K8sCortex sits in between: it decides, per person and per cluster, which of its 75 tools may run, and records every call. Clusters from different clouds live in one registry, with credentials minted on demand.

A real Claude Code session with K8sCortex as its only tool, on a throwaway prod cluster: the developer is denied the rollback, the release manager is blocked by the prod policy, the SRE fixes it. [Watch all five scenarios (97 s)](docs/demo/claude/claude-demo.mp4): incident, release drift, flash-sale scaling, password rotation, node maintenance. How it was recorded.


Features

  • Curated multi-domain toolset across workload, deployment, configuration, observability, jobs, networking, GitOps, cluster admin, and generic read paths
  • Multi-cloud cluster providers — kubeconfig contexts, Amazon EKS (IAM/IRSA), Google GKE (Workload Identity) and Azure Key Vault, mixed in one registry
  • Multi-cluster routing — target any registered cluster with a single cluster parameter; writes require an explicit cluster when several are registered
  • Any OIDC identity provider (Entra ID, Okta, Cognito, Keycloak, Google) with per-tool RBAC (5-tier role hierarchy) and per-cluster policies
  • Structured audit logging — every tool call recorded with caller identity, arguments, and outcome
  • Dual transport — SSE/HTTP for programmatic clients + stdio for Claude Desktop
  • Short-lived credentials — EKS and GKE tokens are minted on demand and cached only until they expire
  • Dry-run safety — destructive tools default to simulation mode
  • Generic read coverage — list/get support for resources outside curated write paths to avoid troubleshooting dead-ends

Install

Claude Desktop, Claude Code, Cursor and other MCP clients (stdio)

Requires Node.js 22+ and a working kubeconfig. Add to your client's MCP configuration (Claude Desktop: claude_desktop_config.json):

{

"mcpServers": { "k8scortex": { "command": "npx", "args": ["-y", "k8scortex-mcp"], "env": { "K8SCORTEX_STDIO_ROLES": "developer" } } } }

developer gives a read-only session; remove it for the full toolset. With Claude Code: claude mcp add k8scortex -- npx -y k8scortex-mcp.

As a shared service for a team (HTTP + OIDC)

With the Helm chart (read-only RBAC by default; see the chart README for writes and more clouds):

helm install k8scortex ./charts/k8scortex -n platform-mcp --create-namespace \

--set auth.oidc.issuer=https://login.example.com --set auth.oidc.audience=k8scortex

Plain manifests rendered from the chart are in kubernetes/. Or run the image directly:

docker run -p 3000:3000 \

-e OIDC_ISSUER=https://login.example.com -e OIDC_AUDIENCE=k8scortex \ -e CLUSTERS_CONFIG=/config/clusters.json -v "$PWD/clusters.json:/config/clusters.json:ro" \ ghcr.io/apatilgtn/k8scortex-mcp:latest

Run it in a management cluster with Workload Identity / IRSA / managed identity for the cloud providers, expose /mcp internally, and ship the audit log to your SIEM. See Multi-cloud setup and Authentication.

Develop

Prerequisites
  • Node.js ≥ 22 (the GKE provider's google-auth-library and the jose dependency of jwks-rsa need it)
  • A Kubernetes cluster (minikube, kind, GKE, EKS, AKS or OpenShift)
  • kubectl configured with a valid context
Install & Run
# Clone

git clone https://github.com/apatilgtn/k8scortex-mcp.git cd k8scortex-mcp

Install

npm install

Build

npm run build

Run (local dev mode — auth bypassed)

DISABLE_AUTH=true PORT=3001 npm run dev

Connect with MCP Inspector
npx @modelcontextprotocol/inspector sse http://localhost:3001/mcp
Connect Claude Desktop to a local build

Point the client at your build instead of the npm package:

{

"mcpServers": { "k8scortex": { "command": "node", "args": [" /k8scortex-mcp/dist/stdio.js"] } } }

Restart Claude Desktop. Ask: *"List all pods in the default namespace"*.

Every context in your kubeconfig is available as a cluster, so you can ask *"Compare the web app's ArgoCD revision between kind-dev and prod-eks"*. Set K8SCORTEX_STDIO_ROLES=developer to give the local session read-only tools.


Multi-cloud setup

K8sCortex picks its cluster source from the environment:

SourceWhenClusters
CLUSTERS_CONFIG=/path/clusters.jsonSetClusters listed in the file, across any providers
Azure Key VaultAZURE_KEYVAULT_URI setThe Key Vault cluster index
kubeconfigOtherwise (or USE_LOCAL_KUBECONFIG=true)Every context in KUBECONFIG / ~/.kube/config, or the in-cluster service account

DEFAULT_CLUSTER chooses the cluster used when a tool call names none. Read-only tools fall back to it; mutating tools require an explicit cluster whenever more than one cluster is registered.

Cluster registry file
{

"defaultCluster": "dev", "clusters": [ { "name": "dev", "provider": "kubeconfig", "context": "kind-dev", "labels": { "env": "dev" } }, { "name": "prod-eks", "provider": "eks", "region": "us-east-1", "eksClusterName": "prod", "roleArn": "arn:aws:iam::111122223333:role/k8scortex", "labels": { "env": "prod" } }, { "name": "prod-gke", "provider": "gke", "project": "my-project", "location": "us-central1", "gkeClusterName": "prod", "labels": { "env": "prod" } }, { "name": "prod-aks", "provider": "azure-keyvault", "cloud": "aks", "region": "australiaeast", "keyVaultUri": "https://my-vault.vault.azure.net", "labels": { "env": "prod" } } ], "policies": [ { "labels": { "env": "prod" }, "minRole": "sre", "appliesTo": "mutating" }, { "match": "prod-*", "denyTools": ["drain_node", "delete_namespace"] } ] }

ProviderCredentialsFields
kubeconfigWhatever the context uses, including exec plugins (aws eks get-token, gke-gcloud-auth-plugin, kubelogin)context, kubeconfigPath
eksDefault AWS chain (IRSA, EKS Pod Identity, instance profile, env, SSO), optionally assuming roleArn; tokens are presigned STS URLs refreshed every 14 minutesregion, eksClusterName, roleArn
gkeApplication Default Credentials (GKE Workload Identity, service account, gcloud auth application-default login)project, location, gkeClusterName, usePrivateEndpoint
azure-keyvaultManaged identity; base64 kubeconfig in secret kubeconfig- (or secretName)keyVaultUri, secretName

The EKS and GKE providers use optional dependencies (@aws-sdk/client-eks, @aws-sdk/credential-providers, @smithy/signature-v4, @aws-crypto/sha256-js, google-auth-library) that npm installs by default. The identity needs eks:DescribeCluster plus an EKS access entry, or container.clusters.get plus Kubernetes RBAC on GKE.

Per-cluster policies

Policies match clusters by name glob (match) and/or labels, and can only tighten the global role table:

  • minRole raises the role required on matching clusters (appliesTo: "mutating" limits it to write tools)
  • denyTools disables tools for everyone on matching clusters

compare_clusters is checked against both clusters it reads.

Authentication

HTTP mode refuses to start unless an identity provider is configured (or DISABLE_AUTH=true):

VariableDescription
OIDC_ISSUERIssuer URL(s), comma-separated; JWKS is discovered from /.well-known/openid-configuration
OIDC_AUDIENCEExpected audience(s), comma-separated
OIDC_JWKS_URIOptional JWKS URL override
OIDC_ROLES_CLAIMClaim holding roles/groups (default roles; e.g. groups, cognito:groups, realm_access.roles)
OIDC_ROLE_MAPJSON map from IdP group names to K8sCortex roles, e.g. {"k8s-admins":"platform-engineer"}
ENTRA_TENANT_ID / ENTRA_CLIENT_IDShorthand for Entra ID (sets issuer, audience and JWKS)

Tools

K8sCortex intentionally keeps writes curated and governed, while allowing flexible read access for diagnostics.

DomainToolDescription
Workloadlist_podsList pods with status and IP
Workloadget_pod_logsFetch container logs
Workloaddescribe_deploymentFull deployment spec
Workloadlist_statefulsetsList StatefulSets with rollout status
Workloaddescribe_statefulsetDetailed StatefulSet spec/status
Workloadlist_daemonsetsList DaemonSets with scheduling status
Workloaddescribe_daemonsetDetailed DaemonSet spec/status
Workloadlist_nodesCluster nodes with Ready status
Deployscale_deploymentScale replicas (dry-run default)
Deployrestart_podDelete pod to trigger restart
Configget_configmapRead ConfigMap data
Configdescribe_namespace_quotaResource quota usage
Configlist_eventsRecent namespace events
Configlist_persistent_volume_claimsPVC status, bound volume, storage class, capacity
Configget_effective_permissionsServiceAccount SubjectAccessReview matrix
Generic Readlist_k8s_resourcesGeneric list for arbitrary resource kinds
Generic Readget_k8s_resourceGeneric get for arbitrary resource kinds
Observeget_hpa_statusHPA metrics and scaling
Observelist_warning_eventsWarning events for triage
Observeget_node_pressureNode memory/disk/PID pressure
Multilist_clustersAll registered clusters
Multiget_cluster_infoNode count, versions, architecture

For the evolving full catalog, see docs/developer-guide.md.


Managed Risk

The largest functional risk in Kubernetes MCP is dead-end visibility on non-curated resources (for example StatefulSets, DaemonSets, PVCs, or CRDs). K8sCortex addresses this by combining:

  • Governed writes: high-impact operations remain explicit, role-gated, and often dry-run by default.
  • Flexible reads: generic read tools cover arbitrary resource kinds for diagnostics.

This keeps the governance posture strong while preserving practical troubleshooting coverage.


Scope Boundaries (v1)

K8sCortex is designed as a governed platform interface, not an unrestricted Kubernetes super-client.

  • Generic write for any resource: intentionally out of scope in v1. Writes are curated and role-gated by design.
  • Pod exec interactive sessions: intentionally out of scope in v1. This requires stronger session controls and command-level auditing that are planned for a later version.

Architecture

Claude / IDE agents / CI-CD

│ ▼ ┌───────────────────────────

Only the beginning is shown; read the rest in the repo

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