JMeter MCP Server

This is a Model Context Protocol (MCP) server that allows executing JMeter tests through MCP-compatible clients and analyzing test results.

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# JMeter Configuration JMETER_HOME=/path/to/apache-jmeter-5.6.3 JMETER_BIN=${JMETER_HOME}/bin/jmeter # Optional: JMeter Java options JMETER_JAVA_OPTS="-Xms1g -Xmx2g"

{ "mcpServers": { "jmeter": { "command": "/path/to/uv", "args": [ "--directory", "/path/to/jmeter-mcp-server", "run", "jmeter_server.py" ] } } }

- Run JMeter tests in non-GUI mode for better performance
- Launch JMeter in GUI mode for test development
- Generate JMeter report dashboards

- Analyze JTL files to understand performance characteristics
- Identify performance bottlenecks and their severity
- Get actionable recommendations for performance improvements
- Generate visualizations for better understanding of results
- Create comprehensive HTML reports for sharing with stakeholders

- Validate that the test file exists
- Check that the file has a .jmx extension
- Validate that JTL files exist and have valid formats
- Capture and return any execution or analysis errors

The Test Results Analyzer is a powerful feature that helps you understand your JMeter test results better. It consists of several components:

- Supports both XML and CSV JTL formats
- Efficiently processes large files with streaming parsers
- Validates file formats and handles errors gracefully

- Calculates overall performance metrics (average, median, percentiles)
- Provides endpoint-specific metrics for detailed analysis
- Generates time series metrics to track performance over time
- Compares metrics with benchmarks for context

- Identifies slow endpoints based on response times
- Detects error-prone endpoints with high error rates
- Finds response time anomalies and outliers
- Analyzes the impact of concurrency on performance

- Provides specific recommendations for addressing bottlenecks
- Analyzes error patterns and suggests solutions
- Generates insights on scaling behavior and capacity limits
- Prioritizes recommendations based on potential impact

- Creates time series graphs showing performance over time
- Generates distribution graphs for response time analysis
- Produces endpoint comparison charts for identifying issues
- Creates comprehensive HTML reports with all analysis results

# Run a JMeter test and generate a results file Run JMeter test sample_test.jmx in non-GUI mode and save results to results.jtl # Analyze the results Analyze the JMeter test results in results.jtl and provide detailed insights # Identify bottlenecks What are the performance bottlenecks in the results.jtl file? # Get recommendations What recommendations do you have for improving performance based on results.jtl? # Generate visualizations Create a time series graph of response times from results.jtl

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