Compresses log files into templates and statistics using Drain3, and exposes them to AI assistants via an MCP server for efficient log monitoring and anomaly detection.
Enables AI agents such as Cursor and Claude Code to inspect local log files through MCP tools for tailing, searching, filtering, statistics, and root-cause diagnosis using local Ollama or a built-in rule engine.
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.
A persistent activity log server that allows MCP-compatible AI assistants to log events, decisions, and system logs over HTTP, with a built-in web dashboard for monitoring and searching logs.