analyze_logs
Extract error patterns from log text
How to use it
analyze_logs is exposed by the Lumino MCP Server MCP server. Add the server to your MCP client (Claude Desktop, Cursor, Windsurf and others), and the analyze_logs tool becomes available to the model automatically. See the full listing for setup details and every tool this server provides.
Install Lumino MCP Server
pip install -e .Other tools in Lumino MCP Server (39)
Dynamic investigation based on query
ML-powered event pattern detection
Root cause analysis for failed pipelines
Combined analysis strategies
Automated incident reports
Certificate expiry monitoring
Detect resource issues in namespace
Pipeline performance baselines
Focused namespace health check
Classify log templates into golden signals and fault categories using zero-shot ML (requires optional logan dependency)
Statistical anomaly detection
Anomaly detection with severity levels
Find pipelines by pattern matching
etcd log retrieval and analysis
Get any Kubernetes resource with flexible output
MachineConfigPool status and updates
Cluster operator health
Retrieve pipeline logs with optional cleaning
Cluster-wide pipeline status summary
Find TLS-related problems
List all namespaces in the cluster
List PipelineRuns with status and timing
List pods with status and placement info
Recent pipelines across all namespaces
List TaskRuns, optionally filtered by pipeline
Real-time system topology mapping
Manage training data for predictive log analyzer
Trace pipelines by commit, PR, or image
Predict issues from log patterns
Multi-level event analysis
Execute PromQL queries
Query archived Kubernetes resources from KubeArchive with optional log retrieval
Predict resource exhaustion
Search resources across namespaces by labels
NLP-based semantic log search
Smart event retrieval with strategies
Intelligent log summarization
Streaming analysis for large logs
Cluster logs into unique structural templates using Drain3 (requires optional logan dependency)