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JMeter MCP Server

@QAInsights

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基本信息

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QAInsights

关于 JMeter MCP Server

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

#jmeter#performance-testing#load-testing

JMeter MCP Server 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"
      ]
    }
  }
}

JMeter MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

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

常见问题

1

What are the prerequisites?

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

2

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.

3

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`.

4

Does the server support GUI‑mode execution?

Yes, the `execute_jmeter_test` tool launches JMeter in GUI mode, but it does not run the test – that matches standard JMeter behavior.

5

What JTL file formats are supported for analysis?

Both XML and CSV JTL formats are supported. The parser uses streaming parsers for efficient processing of large files.

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