Parallel Sort

claude mcp add --scope project clio-parallel-sort -- clio-kit mcp-server parallel-sort

Install the launcher first. Restart your client after setup. Configuration locations →

clio-kit doctor --server parallel-sort --connect

Tools​

sort_log_by_timestamp

Sort log file lines by timestamps in YYYY-MM-DD HH:MM:SS format.

parallel_sort_large_file

Sort large log files using parallel processing with chunked approach.

analyze_log_statistics

Generate statistics for log files including temporal patterns and log levels.

detect_log_patterns

Detect patterns in log files including anomalies and error clusters.

filter_logs

Filter log entries based on multiple conditions with logical operations.

filter_by_time_range

Filter log entries by time range using start and end timestamps.

filter_by_log_level

Filter log entries by log level (ERROR, WARN, INFO, DEBUG, etc.).

filter_by_keyword

Filter log entries by keywords with support for multiple keywords and logical operations.

apply_filter_preset

Apply predefined filter presets like 'errors_only' or 'connection_issues'.

export_to_json

Export log processing results to JSON format.

export_to_csv

Export log entries to CSV format with structured columns.

export_to_text

Export log entries to plain text format.

generate_summary_report

Generate a summary report of log processing results with statistics.

Examples​

Replace example paths with your own files and check the returned results.

Sorting and filtering return previews of at most 100 lines and 16,384 UTF-8 bytes. Check truncated and total_result_lines. Set output_file to save every result line; without it, a truncated result has not been saved.

1. Large Log File Sorting and Analysis​

I have a large application log file at /var/logs/app.log with millions of entries. Sort this log chronologically and analyze the error patterns.

Tools called:

• parallel_sort_large_file - Sort the large log file using parallel processing
• analyze_log_statistics - Analyze log statistics and patterns
• detect_log_patterns - Detect error patterns and anomalies

This prompt will:

• Use parallel_sort_large_file to efficiently sort the large log file with optimal chunk processing
• Analyze log statistics using analyze_log_statistics for comprehensive metrics
• Detect patterns using detect_log_patterns to identify issues and trends
• Generate sorted output with detailed analysis reports

2. Error Log Filtering and Export​

Filter all ERROR and WARN level entries from /var/logs/system.log from the last 24 hours and export to CSV for analysis.

Tools called:

• filter_by_time_range - Filter logs by time range
• filter_by_log_level - Filter by ERROR and WARN levels
• export_to_csv - Export filtered results to CSV

This prompt will:

• Filter logs by time range using filter_by_time_range for the last 24 hours
• Apply log level filtering using filter_by_log_level for ERROR and WARN entries
• Export results using export_to_csv with structured columns
• Provide filtered dataset ready for analysis

3. Connection Issue Pattern Detection​

Analyze /var/logs/network.log for connection timeout patterns and generate a comprehensive report with trend analysis.

Tools called:

• filter_by_keyword - Filter for connection-related entries
• detect_log_patterns - Detect timeout patterns and trends
• generate_summary_report - Create comprehensive analysis report

This prompt will:

• Filter connection-related entries using filter_by_keyword with timeout keywords
• Analyze patterns using detect_log_patterns for anomaly detection
• Generate comprehensive report using generate_summary_report
• Provide trend analysis and proactive issue identification

4. Multi-Condition Log Analysis​

Find all database connection errors in /var/logs/db.log that occurred during business hours (9 AM - 5 PM) and contain "timeout" or "refused".

Tools called:

• filter_by_time_range - Filter for business hours
• filter_by_keyword - Filter for timeout and connection refused
• filter_logs - Apply complex multi-condition filtering
• analyze_log_statistics - Analyze filtered results

This prompt will:

• Apply time-based filtering using filter_by_time_range for business hours
• Filter by keywords using filter_by_keyword for timeout and refused conditions
• Combine filters using filter_logs with logical operators
• Analyze results using analyze_log_statistics for comprehensive insights

5. Log Quality Assessment and Cleanup​

Analyze the quality of /var/logs/application.log, identify malformed entries, and generate a clean sorted version with quality metrics.

Tools called:

• analyze_log_statistics - Assess log quality and identify issues
• sort_log_by_timestamp - Sort logs chronologically
• generate_summary_report - Create quality assessment report

This prompt will:

• Assess log quality using analyze_log_statistics with quality metrics
• Sort logs using sort_log_by_timestamp for chronological order
• Generate quality report using generate_summary_report
• Provide clean dataset with quality improvement recommendations

6. Historical Log Trend Analysis​

Analyze error trends in /var/logs/historic.log over the past month, detect anomalies, and export findings to JSON for dashboard integration.

Tools called:

• filter_by_time_range - Filter for past month
• detect_log_patterns - Detect trends and anomalies
• analyze_log_statistics - Generate temporal analysis
• export_to_json - Export results for dashboard

This prompt will:

• Filter historical data using filter_by_time_range for the past month
• Detect trends using detect_log_patterns with anomaly detection
• Analyze temporal patterns using analyze_log_statistics
• Export findings using export_to_json for dashboard integration