Log Analysis SQLite

Transforms compressed log files into a queryable SQLite database with tables for logs, stack traces, and errors, enabling efficient analysis and troubleshooting of application issues by timestamp, log level, and module.

This SQLite MCP server implementation enables AI assistants to analyze log files by creating and querying a structured database from compressed log data. It processes gzipped log files into an SQLite database with tables for logs, stack traces, and parsing errors, while providing tools to extract error data to Parquet format for further analysis. The server supports querying by log level, timestamp, and module, making it valuable for troubleshooting application issues, identifying error patterns, and generating insights from large volumes of log data.