Provides advanced forensic analysis of JVM Flight Recorder (JFR) data for integration with large language models.
Sponsored
Lumen serves as the analytical core of the Lumen ecosystem, leveraging a high-performance Java engine to meticulously parse JVM Flight Recorder (JFR) files. A TypeScript bridge seamlessly integrates this capability, offering a Model Context Protocol (MCP) interface specifically designed for AI agents such as Gemini and Claude. This hybrid server facilitates deep JVM analysis, enabling the identification of performance bottlenecks, elusive exceptions, and resource consumption patterns crucial for optimizing Java applications and informing AI-driven diagnostic processes.
主な機能
01Combines Java's deep JFR parsing power with Node.js's ecosystem compatibility for hybrid intelligence.
02Traces hidden exceptions (Swallowed Exceptions) with full call chains for comprehensive forensics.
03Pinpoints slow SQL queries and socket latencies with line-level precision.
04Fully compatible with Smithery CLI for instant distribution and deployment.
05Identifies hot methods consuming the most CPU cycles and analyzes memory usage hotspots.
060 GitHub stars
ユースケース
01Diagnosing database response slowness by analyzing JFR data.
02Identifying and tracing hidden exceptions and their call chains in JVM applications.
03Pinpointing code lines that are consuming the most CPU cycles or causing memory allocation issues.
