🚀 JMeter MCP Server

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

📋 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

Related MCP server: MCP Server

🛠️ Installation

Local Installation

1. Install 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:

chmod +x /path/to/jmeter/bin/jmeter

3. Install required Python dependencies:

pip install -r requirements.txt

4. 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"

💻 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:

{
    "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