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Lumino MCP Server

Unclaimed

by spre-sre

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.

Install

$pip install -e .

Set up this server

This server needs project-specific setup. Follow the project instructions; no reusable public launch command is available yet.

Project instructions

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40 of 40 tools

Documented tools (40)

From project documentation. A server handshake does not verify each tool’s description or behavior.

adaptive_namespace_investigation

Dynamic investigation based on query

advanced_event_analytics

ML-powered event pattern detection

analyze_failed_pipeline

Root cause analysis for failed pipelines

analyze_logs

Extract error patterns from log text

analyze_pod_logs_hybrid

Combined analysis strategies

automated_triage_rca_report_generator

Automated incident reports

check_cluster_certificate_health

Certificate expiry monitoring

check_resource_constraints

Detect resource issues in namespace

ci_cd_performance_baselining_tool

Pipeline performance baselines

conservative_namespace_overview

Focused namespace health check

deep_analyze_pod_logs

Classify log templates into golden signals and fault categories using zero-shot ML (requires optional logan dependency)

detect_anomalies

Statistical anomaly detection

detect_log_anomalies

Anomaly detection with severity levels

find_pipeline

Find pipelines by pattern matching

get_etcd_logs

etcd log retrieval and analysis

get_kubernetes_resource

Get any Kubernetes resource with flexible output

get_machine_config_pool_status

MachineConfigPool status and updates

get_openshift_cluster_operator_status

Cluster operator health

get_pipelinerun_logs

Retrieve pipeline logs with optional cleaning

get_tekton_pipeline_runs_status

Cluster-wide pipeline status summary

investigate_tls_certificate_issues

Find TLS-related problems

list_namespaces

List all namespaces in the cluster

list_pipelineruns

List PipelineRuns with status and timing

list_pods_in_namespace

List pods with status and placement info

list_recent_pipeline_runs

Recent pipelines across all namespaces

list_taskruns

List TaskRuns, optionally filtered by pipeline

live_system_topology_mapper

Real-time system topology mapping

manage_prediction_training_data

Manage training data for predictive log analyzer

pipeline_tracer

Trace pipelines by commit, PR, or image

predictive_log_analyzer

Predict issues from log patterns

progressive_event_analysis

Multi-level event analysis

prometheus_query

Execute PromQL queries

query_kubearchive

Query archived Kubernetes resources from KubeArchive with optional log retrieval

resource_bottleneck_forecaster

Predict resource exhaustion

search_resources_by_labels

Search resources across namespaces by labels

semantic_log_search

NLP-based semantic log search

smart_get_namespace_events

Smart event retrieval with strategies

smart_summarize_pod_logs

Intelligent log summarization

stream_analyze_pod_logs

Streaming analysis for large logs

templatize_pod_logs

Cluster logs into unique structural templates using Drain3 (requires optional logan dependency)

Tool change history

Compared across complete checks of the same configuration. Tools were listed, not invoked. Input-schema changes are not measured here.

No complete tool checks yet.

FAQ

Questions about Lumino MCP Server

How do I connect Lumino MCP Server to Claude?
The listing records `pip install -e .` as its setup step. Run it, then follow the repository's instructions for the client configuration; the listing names Claude Desktop, Claude Code, Cursor as compatible clients.
Is Lumino MCP Server free?
The listed licence is Apache-2.0. Check the upstream terms for permitted use and commercial requirements; a public repository does not by itself mean the software is free or open source. Connected APIs and hosted services may have separate charges.
What can Lumino MCP Server do?
Lumino MCP Server documents 40 tools to the agent, including adaptive_namespace_investigation, advanced_event_analytics, analyze_failed_pipeline. The descriptions above come from project documentation. A live handshake does not test individual tool behavior.