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janus-mcp-server
Advanced tools
Secure Kubernetes MCP server: redacted diagnostics and human-approved writes, credentials never leave the process.
Two faces. One cluster. No exposed keys.
janus-mcp.ns47.com · PyPI · Changelog
Janus is an MCP (Model Context Protocol) server that gives AI assistants a safe, controlled window into your Kubernetes clusters. It runs locally, holds your KUBECONFIG close to its chest, and lets the LLM operate through carefully‑scoped tools — so you get the power of an AI copilot without ever shipping a token, certificate, or API server URL to a third‑party model.
Named after the Roman god of gateways (who famously looks both ways at once), Janus faces the LLM with clean, declarative tool definitions, and faces your cluster with full administrative access — while ensuring the two never meet inappropriately.
LLMs are incredibly useful for debugging, operating, and reasoning about Kubernetes. But the moment you paste a KUBECONFIG into a chat window or send it to an external API, you’ve handed over the keys to your kingdom. For most organisations, that’s a non‑starter.
Self‑hosting a model helps, but not everyone can or wants to run frontier‑grade LLMs locally. Janus gives you a third path: keep the credentials on‑prem (or on your laptop) and let the remote model work with sanitised, high‑level cluster information only.
┌──────────────┐ ┌────────────────┐ ┌───────────────┐
│ LLM Client │<─────>│ Janus (local) │<─────>│ Kubernetes │
│ (Claude, │ MCP │ holds the │ k8s │ API Server │
│ VS Code, │ │ KUBECONFIG │ API │ │
│ custom) │ │ redacts output │ │ │
└──────────────┘ └────────────────┘ └───────────────┘
get_pods, describe_deployment, get_events, etc.) that the LLM can call. It never hands over raw cluster state.KUBECONFIG permits.KUBECONFIG never leaves the process running Janus.kubectl top+), and rollout history with sanitized template diffs (“what changed recently?”).get_cluster_summary tool, plus a pinnable cluster://summary MCP resource that gives the LLM context without a flurry of tool calls.diagnose_namespace prompt template walks the model through a structured investigation (overview → pods → warnings → targeted logs → diagnosis) in any client that supports MCP prompts.janus-mcp-server · container ghcr.io/tonylchang/janus-mcp · Homebrew tonylchang/tap/janus-mcpuv tool install janus-mcp-server # or: pipx install janus-mcp-server
# brew install tonylchang/tap/janus-mcp
mkdir -p ~/.config/janus-mcp
curl -fsSL https://raw.githubusercontent.com/tonylchang/janus-mcp/main/examples/config.yaml \
-o ~/.config/janus-mcp/config.yaml
$EDITOR ~/.config/janus-mcp/config.yaml # set your kubeconfig context + namespaces
# register with Claude Code:
claude mcp add kubernetes -- janus-mcp serve
No Python toolchain? The same server ships as a container image:
claude mcp add kubernetes -- docker run -i --rm \
-v ~/.kube/config:/home/janus/.kube/config:ro \
-v ~/.config/janus-mcp:/home/janus/.config/janus-mcp:ro \
ghcr.io/tonylchang/janus-mcp:latest
Registration recipes for Claude Desktop, VS Code/Copilot, Codex CLI, and Cursor are in the quick start guide.
Now ask your AI assistant something like: “Why are pods crashing in the prod namespace?”
Janus will fetch the relevant information, sanitise it, and the LLM will walk you through what’s happening — safely.
rbac/ — least-privilege manifests (note what is absent: secrets — nowhere, ever)Janus is currently in active development.
FAQs
Secure Kubernetes MCP server: redacted diagnostics and human-approved writes, credentials never leave the process.
We found that janus-mcp-server demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.

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