AI/ML-powered diagnostic engine for SRE Observability on Konflux and OpenShift. It uses the Model Context Protocol (M...
Copy the install, test the workflow, then decide if it earns a permanent slot.
Still active enough to matter. Good candidate for a fast stack test instead of a long evaluation loop.
Copy the install, test the workflow, then decide if it earns a permanent slot.
You can test this quickly and remove it cleanly if it misses.
GitHub health 87/100. no security policy. Fresh enough repo health and manageable issue load keep the risk controlled.
AI Agent
Universal
Model
Multiple
Fastest way to find out if lumino-mcp-server belongs in your setup.
Copy the install command, run a real test, and back it out cleanly if it slows you down.
claude mcp add lumino-mcp-server -- npx lumino-mcp-serverRun this first. You will know quickly if the workflow earns a permanent slot.
claude mcp remove lumino-mcp-serverNo messy cleanup loop. If it misses, remove it and keep moving.
Install Location
~/ └─ .claude.json └─ mcp_servers/ └─ lumino-mcp-server ← registers here
AI/ML-powered diagnostic engine for SRE Observability on Konflux and OpenShift. It uses the Model Context Protocol (MCP) and 40+ tools to analyze logs, metrics, and traces, enabling automated RCA and predictive analysis.
Source: GitHub repository
Source check: July 18, 2026
Upstream commit: July 14, 2026
Repository state: Not marked archived
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