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KSail

KSail

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ksail.devantler.techCloud & Infra164Updated today

About KSail

KSail is a toolkit for creating Kubernetes clusters, deploying applications, and handling routine operations from a terminal, VS Code, or an AI assistant. It combines local and supported cloud cluster workflows with deployment, configuration, and operations tools.

Key features

  1. 01Create local and supported cloud clusters
  2. 02Deploy with kubectl, Helm, Kustomize, Flux, and ArgoCD
  3. 03Encrypt secrets with SOPS and Age
  4. 04Validate manifests with Kubeconform
  5. 05Support backups, restores, and multi-tenancy
  6. 06Provide a chat assistant and VS Code extension

Use cases

  1. 01Create and explore a local Kubernetes cluster
  2. 02Deploy applications to a Kubernetes cluster
  3. 03Protect secrets and validate manifests
  4. 04Back up or restore clusters

MCP support

KSail includes an MCP server for AI assistants to work with its Kubernetes capabilities.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"devantler-tech-ksail": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/devantler-tech/ksail:v7.206.36"
]
}
}
}
Run commanddocker run -i --rm ghcr.io/devantler-tech/ksail:v7.206.36

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
ocighcr.io/devantler-tech/ksail:v7.206.36

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

GitHub Stars Latest Release License Go Reference CI - KSail

🛥️🐳 KSail

KSail command-line interface

KSail brings Kubernetes cluster setup, application deployment and everyday operations into one tool. Create local clusters with Docker, or work with supported cloud providers and existing Kubernetes clusters. Use it from your terminal, VS Code or an AI assistant.

📖 Documentation · Quickstart · Support

What you get

TaskIncluded tools and capabilities
Create clustersKind, K3d, Talos, vCluster, KWOK, EKS, GKE and AKS
Deploy applicationskubectl, Helm, Kustomize, Flux and ArgoCD
Protect configurationEncrypt secrets with SOPS and Age; validate manifests with Kubeconform
Operate clustersK9s, backup and restore, multi-tenancy
Work with AIChat assistant, MCP server and VS Code extension

See features and the support matrix for supported platforms and combinations. KWOK simulates clusters; it does not run applications. Cloud providers need their own setup and incur charges.

Quick install

On Linux or an Apple Silicon Mac, with curl, tar and sha256sum or shasum available:

curl -fsSL https://github.com/devantler-tech/ksail/releases/latest/download/install.sh | sh

The installer verifies the download and prints where it installed KSail. Follow its PATH instruction if needed. Prefer Homebrew or a Windows download? See installation options.

Quick start

Create a project in a new directory:

mkdir my-app
cd my-app
ksail project init --name my-app --distribution Vanilla --provider Docker

This creates your project files without needing Docker or a cloud account. With Docker Engine or Docker Desktop running, start and explore a local cluster:

ksail cluster create
ksail cluster connect

This creates a local Kubernetes cluster and opens K9s to explore it. Enter :quit to leave K9s. When finished, delete the trial cluster and its applications:

ksail cluster delete --name my-app --provider Docker

Review the cluster name and confirm deletion when prompted. Project files remain for reuse.

Continue with the quickstart guide to deploy an application. The reader reference covers local setup details, cloud providers and optional AI assistant plugins.

Community & support

License

KSail is source-available under PolyForm Shield 1.0.0, with use, redistribution and noncompetition terms. See the licensing guide and full license before reusing it.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.