JMeter MCP Server

JMeter MCP Server

Enables the execution and analysis of JMeter performance tests through MCP-compatible clients. It provides tools for running tests in non-GUI mode, identifying performance bottlenecks, and generating comprehensive insights and visualizations from result files.

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README

šŸš€ 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] šŸ“¢ Looking for an AI Assistant inside JMeter? šŸš€ Check out Feather Wand

Anthropic Cursor Windsurf

šŸ“‹ Features

JMeter Execution

  • šŸ“Š Execute JMeter tests in non-GUI mode
  • šŸ–„ļø Launch JMeter in GUI mode
  • šŸ“ Capture and return execution output
  • šŸ“Š Generate JMeter report dashboard

Test Results Analysis

  • šŸ“ˆ Parse and analyze JMeter test results (JTL files)
  • šŸ“Š Calculate comprehensive performance metrics
  • šŸ” Identify performance bottlenecks automatically
  • šŸ’” Generate actionable insights and recommendations
  • šŸ“Š Create visualizations of test results
  • šŸ“‘ Generate HTML reports with analysis results

šŸ› ļø Installation

Local Installation

  1. Install uv:

  2. Ensure JMeter is installed on your system and accessible via the command line.

āš ļø Important: Make sure JMeter is executable. You can do this by running:

chmod +x /path/to/jmeter/bin/jmeter
  1. Install dependencies and run the server:
uv sync
  1. Configure the .env file, refer to the .env.example file for details.
# 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"

šŸ’» 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
  1. MCP compatible client will use the available tools:

JMeter Execution Tools

  • šŸ–„ļø execute_jmeter_test: Launches JMeter in GUI mode, but doesn't execute test as per the JMeter design
  • šŸš€ execute_jmeter_test_non_gui: Execute a JMeter test in non-GUI mode (default mode for better performance)

Test Results Analysis Tools

  • šŸ“Š analyze_jmeter_results: Analyze JMeter test results and provide a summary of key metrics and insights
  • šŸ” identify_performance_bottlenecks: Identify performance bottlenecks in JMeter test results
  • šŸ’” get_performance_insights: Get insights and recommendations for improving performance
  • šŸ“ˆ generate_visualization: Generate visualizations of JMeter test results

šŸ—ļø MCP Configuration

Add the following configuration to your MCP client config:

{
    "mcpServers": {
      "jmeter": {
        "command": "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

šŸ›‘ 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

šŸ“Š 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

šŸ“ 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

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