Lumino MCP Server
Give your coding agent live Kubernetes and OpenShift cluster context, Tekton pipeline forensics, and SRE-style root-cause hints without leaving the IDE.
Overview
Lumino is a MCP server for the Operate phase that brings AI-powered SRE observability and 40+ Tekton debugging tools to Kubernetes and OpenShift from your agent.
What is this MCP server?
- 40+ Tekton-focused debugging tools for CI/CD pipeline failures on Kubernetes and OpenShift
- AI-assisted SRE observability: log analysis and root-cause analysis oriented workflows
- Predictive monitoring signals for cluster and pipeline health
- Stdio MCP via PyPI package lumino-mcp-server (uvx), Apache-2.0, Python stack
- Authenticates with KUBECONFIG (~/.kube/config) for real cluster operations
- 40+ Tekton debugging tools (publisher description)
- Server version 0.9.2; Apache-2.0 license; Python; stdio via uvx
What problem does it solve?
Pipeline and cluster failures on K8s force you to context-switch across logs, Tekton runs, and kubectl commands while your agent stays blind to the live system.
Who is it for?
Indie devs or small teams running Tekton on Kubernetes or OpenShift who want agent-driven incident and pipeline debugging with a configured kubeconfig.
Skip if: Builders on serverless-only hosts with no cluster, or anyone who needs a passive dashboard instead of agent-invoked diagnostic tools.
What do I get? / Deliverables
Your agent can investigate Tekton and cluster issues with registry-backed tools so you shorten mean time to understand without building a custom observability MCP yourself.
- Agent-callable cluster and Tekton diagnostic actions from the Lumino tool surface
- Faster structured incident triage context returned into the chat thread
- Repeatable SRE observability workflow without custom MCP authoring
Recommended MCP Servers
Journey fit
Production reliability work—observing clusters, pipelines, and failures—maps to Operate where solo builders who self-host or run K8s need answers fast. Monitoring is the canonical shelf for observability, log analysis, predictive signals, and pipeline debugging on running infrastructure.
How it compares
Cluster SRE MCP integration, not a generic code-review or unit-test skill.
Common Questions / FAQ
Who is Lumino for?
Solo builders and small SRE-minded teams on Kubernetes or OpenShift who want Claude Code, Cursor, or Codex to help debug Tekton pipelines and cluster health.
When should I use Lumino?
Use it during production or CI incidents, flaky pipeline runs, or when you need log analysis and root-cause style investigation on a live cluster.
How do I add Lumino to my agent?
Register the stdio MCP server (PyPI lumino-mcp-server, runtimeHint uvx), set KUBECONFIG to your kube config path, and connect it in your agent’s MCP settings.