🚀 JMeter MCP Server

Name: 🚀 JMeter MCP Server
Author: QAInsights

@QAInsights

代码仓库主页

关于 🚀 JMeter MCP Server

✨ JMeter Meets AI Workflows: Introducing the JMeter MCP Server! 🤯

#jmeter #performance-testing #load-testing

基本信息

分类

其他

运行时

python

传输方式

stdio

发布者

QAInsights

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is 🚀 JMeter MCP Server?

It is a Model Context Protocol (MCP) server that lets MCP-compatible clients (e.g., Claude Desktop, Cursor, Windsurf) execute JMeter tests and analyze results. It is designed for performance testers and developers who want to run and interpret JMeter workloads through natural language prompts.

How to use 🚀 JMeter MCP Server?

Install uv, ensure JMeter is on the system and executable, then install Python dependencies (numpy, matplotlib). Configure the .env file with JMETER_HOME and JMETER_BIN. Connect via an MCP client and use tools like execute_jmeter_test_non_gui, analyze_jmeter_results, identify_performance_bottlenecks, get_performance_insights, and generate_visualization.

Key features of 🚀 JMeter MCP Server

Execute JMeter tests in non‑GUI mode for better performance
Launch JMeter in GUI mode for test development
Parse and calculate comprehensive performance metrics from JTL files
Automatically identify performance bottlenecks and their severity
Generate actionable insights and recommendations
Create visualizations and HTML reports of test results

Use cases of 🚀 JMeter MCP Server

Run JMeter tests in non‑GUI mode with a single prompt
Analyze JTL files to understand performance characteristics
Identify performance bottlenecks and receive severity assessments
Get concrete recommendations for improving performance
Generate HTML reports and visualizations for stakeholder sharing

FAQ from 🚀 JMeter MCP Server

What are the prerequisites?

JMeter must be installed and accessible on the command line. You also need uv and Python dependencies (numpy, matplotlib).

How do I configure the server?

Set JMETER_HOME and JMETER_BIN in the .env file. Optional JMETER_JAVA_OPTS can be added for Java heap settings.

What tools are exposed by the server?

Execution tools: execute_jmeter_test (GUI) and execute_jmeter_test_non_gui. Analysis tools: analyze_jmeter_results, identify_performance_bottlenecks, get_performance_insights, generate_visualization.