Reduces log files to remove noise and duplicate information, cutting tokens by 70-90% for AI agents, preserving only errors, warnings, and unique events.
Captures and stores console output from any process in SQLite with full-text search, enabling AI assistants to search logs, monitor errors, and analyze multi-process activity through natural language queries.
A Python MCP server that reduces token usage by ~98% when working with log files by auto-detecting format and stripping noise to return only actionable signal.
Enables monitoring and analysis of local application log files with real-time tailing, error tracking, and search capabilities. Perfect for debugging Node.js applications, web servers, or any application that writes to log files through natural language commands.
Enables secure analysis of log files by listing, summarizing, and searching for error patterns, with defenses against path traversal, symlink attacks, and data leakage.