JMeter MCP Server

# 🚀 JMeter MCP Server This is a Model Context Protocol (MCP) server that allows executing JMeter tests through MCP-compatible clients and analyzing test results. > [!IMPORTANT] > 📢 Looking for an AI Assistant inside JMeter? 🚀 > Check out [Feather Wand](https://jmeter.ai)    ## 📋 Features ### JMeter Execution - 📊 Execute JMeter tests in non-GUI mode - 🖥️ Launch JMeter in GUI mode - 📝 Capture and return execution output - 📊 Generate JMeter report dashboard ### Test Results Analysis - 📈 Parse and analyze JMeter test results (JTL files) - 📊 Calculate comprehensive performance metrics - 🔍 Identify performance bottlenecks automatically - 💡 Generate actionable insights and recommendations - 📊 Create visualizations of test results - 📑 Generate HTML reports with analysis results ## 🛠️ Installation ### Local Installation 1. Install [`uv`](https://github.com/astral-sh/uv): 2. Ensure JMeter is installed on your system and accessible via the command line. ⚠️ **Important**: Make sure JMeter is executable. You can do this by running: ```bash chmod +x /path/to/jmeter/bin/jmeter ``` 3. Install required Python dependencies: ```bash pip install numpy matplotlib ``` 4. Configure the `.env` file, refer to the `.env.example` file for details. ```bash # 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" ``` ### 💻 MCP Usage 1. Connect to the server using an MCP-compatible client (e.g., Claude Desktop, Cursor, Windsurf) 2. Send a prompt to the server: ``` Run JMeter test /path/to/test.jmx ``` 3. MCP compatible client will use the available tools: #### JMeter Execution Tools - 🖥️ `execute_jmeter_test`: Launches JMeter in GUI mode, but doesn't execute test as per the JMeter design - 🚀 `execute_jmeter_test_non_gui`: Execute a JMeter test in non-GUI mode (default mode for better performance) #### Test Results Analysis Tools - 📊 `analyze_jmeter_results`: Analyze JMeter test results and provide a summary of key metrics and insights - 🔍 `identify_performance_bottlenecks`: Identify performance bottlenecks in JMeter test results - 💡 `get_performance_insights`: Get insights and recommendations for improving performance - 📈 `generate_visualization`: Generate visualizations of JMeter test results ## 🏗️ MCP Configuration Add the following configuration to your MCP client config: ```json { "mcpServers": { "jmeter": { "command": "/path/to/uv", "args": [ "--directory", "/path/to/jmeter-mcp-server", "run", "jmeter_server.py" ] } } } ``` ## ✨ Use Cases ### Test Execution - Run JMeter tests in non-GUI mode for better performance - Launch JMeter in GUI mode for test development - Generate JMeter report dashboards ### Test Results Analysis - 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 ## 🛑 Error Handling The server will: - 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 ## 📊 Test Results Analyzer The Test Results Analyzer is a powerful feature that helps you understand your JMeter test results better. It consists of several components: ### Parser Module - Supports both XML and CSV JTL formats - Efficiently processes large files with streaming parsers - Validates file formats and handles errors gracefully ### Metrics Calculator - 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 ### Bottleneck Analyzer - 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 ### Insights Generator - 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 ### Visualization Engine - 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 ## 📝 Example Usage ``` # 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 ```