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 .

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Tools (40)

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)