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.
An MCP server for intelligent log analysis providing semantic search, error pattern clustering, and smart error detection. It enables users to process, vectorize, and query local logs to efficiently identify issues and generate AI-powered summaries.
An MCP server that gives AI assistants direct access to your Graylog logs -- search, aggregate, analyze, and cluster log data through natural language.
MCP server for collecting and analyzing CLI/web server error logs. Enables watching log files/directories, parsing common error patterns, and querying/analyzing logs through natural language.
A Python-based MCP server that enables AI-assisted log file analysis with features for filtering, parsing, and interpreting log outputs, plus executing and analyzing test runs with varying verbosity levels.