{"repo":"ascii766164696D/log-mcp","free":true,"listed":false,"github":"https://github.com/ascii766164696D/log-mcp","clone":"git clone https://github.com/ascii766164696D/log-mcp.git","description":"MCP server for log file analysis","language":"Python","stars":99,"topics":[],"license":"MIT","category":"mcp-servers","readme_excerpt":"log-mcp MCP server for log file analysis. Gives LLMs the ability to efficiently analyze large log files without loading them into context. This is a tool designed for AI, not humans. No human reads the output of analyze errors or compare logs — Claude does, compresses it further, and gives the human a plain English answer. The human touches two endpoints: \"what's wrong with this log?\" in, natural language answer out. Everything in between is AI talking to itself. Tools Tool Description ------ ------------- log overview Quick scan: size, line count, time range, level distribution, head/tail samples search logs Search by regex, log level, and/or time range get log segment Extract a segment by line range or time range analyze errors Deduplicate errors by fingerprint, count frequencies, extract stack traces log stats Volume histogram, level breakdown, top repeated patterns compare logs Find patterns unique to each file and frequency outliers across files classify lines ML classifier (TF-IDF → BERT) separates interesting lines from noise Key features - ML pre-filter — a Rust TF-IDF classifier scans files at 1.3M lines/sec, so analyze errors and search logs only process the 5-30% of lines that matter. Optional BERT-mini re-scores LOOK lines at 2K lines/sec on Metal GPU for higher precision. Works without parsed log levels — catches errors, security events, hardware faults, and anomalies that don't have ERROR in them. - Auto-detection of log formats: JSON, standard text ( 2024-01-15","default_branch":null,"files":null,"tree":[],"storefront":"/r/ascii766164696D","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/ascii766164696D/log-mcp/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}