Windows ETW Trace Analyzer for Application Performance

An MCP server analyzes Windows ETW (.etl) traces with 54 tools for diagnosing CPU, I/O, memory, network performance, and more.

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Windows ETW Trace Analyzer for Application Performance

This MCP server provides a comprehensive suite of tools for analyzing Windows Event Tracing for Windows (ETW) traces. Designed for developers and performance engineers, it leverages the power of MCP to process .etl files and uncover critical insights into application performance bottlenecks. By examining detailed system events, you can pinpoint issues related to CPU utilization, I/O operations, memory management, network activity, and a wide range of other performance metrics.

What it Does

The Windows ETW Trace Analyzer acts as a central hub for dissecting complex ETW traces. It ingests .etl files and applies 54 distinct analytical tools to extract actionable data. This allows for deep dives into system behavior during application execution, enabling the identification of performance regressions, resource contention, and inefficient code paths. The output is structured to facilitate rapid diagnosis and informed optimization efforts.

Key Features

Comprehensive Analysis: Utilizes 54 specialized tools for in-depth examination of CPU, I/O, memory, and network performance.
ETW Trace Processing: Directly analyzes standard Windows ETW (.etl) trace files.
MCP Server Integration: Leverages the MCP architecture for efficient and scalable trace analysis.
Developer-Focused: Provides technical data essential for debugging and performance tuning.
Root Cause Identification: Aids in pinpointing the underlying causes of performance issues.

Who it's For

This tool is specifically built for AI builders , software developers, system administrators, and performance engineers who need to understand and optimize the performance of applications running on Windows. If you are responsible for diagnosing slow application startup, high resource consumption, or unexpected behavior, this ETW trace analyzer will be an invaluable asset in your toolkit. It is particularly useful for identifying performance regressions introduced by code changes or external system factors.