🚀 Jmeter Mcp 服务器

什么是 JMeter MCP 服务器？

JMeter MCP 服务器是一个创新的解决方案，它将 Apache JMeter 与 AI 工作流程集成，增强了性能测试能力。它允许用户以更高效的方式执行 JMeter 测试，利用人工智能优化测试场景和结果分析。该服务器旨在为希望简化测试流程的开发人员和测试人员提供服务，同时确保高质量的软件交付。

JMeter MCP 服务器的特点

• AI 集成：JMeter MCP 服务器利用 AI 算法分析测试结果，并提供帮助优化测试用例的见解。
• 用户友好的界面：它提供直观的界面，简化了创建和管理测试计划的过程。
• 可扩展性：该服务器可以同时处理多个测试执行，适合大规模测试环境。
• 实时监控：用户可以实时监控测试执行，允许立即调整和故障排除。
• 综合报告：该服务器生成详细报告，提供性能指标的见解，帮助团队做出明智的决策。

如何使用 JMeter MCP 服务器

1. 安装：从官方仓库下载 JMeter MCP 服务器，并按照文档中提供的安装说明进行操作。
2. 配置：根据您的测试需求配置服务器设置。这包括设置测试参数、AI 集成选项和用户权限。
3. 创建测试计划：使用用户友好的界面创建和自定义您的测试计划。您可以定义场景、指定负载条件和设置性能指标。
4. 执行测试：直接从服务器启动您的测试。AI 算法将实时分析执行情况，提供见解和建议。
5. 审查结果：测试执行后，查看服务器生成的综合报告。利用这些见解优化您的应用程序并提高性能。

常见问题解答

Q1: JMeter MCP 服务器的主要目的是什么？

A1: JMeter MCP 服务器的主要目的是通过集成 AI 工作流程来增强性能测试，从而实现更高效的测试执行和分析。

Q2: 我可以使用 JMeter MCP 服务器进行大规模测试吗？

A2: 是的，JMeter MCP 服务器设计用于处理大规模测试环境，支持多个同时测试执行。

Q3: 使用 JMeter MCP 服务器是否需要费用？

A3: JMeter MCP 服务器是一个公共仓库，免费提供。然而，用户可能需要考虑与基础设施和其他工具相关的费用。

Q4: AI 如何改善 JMeter MCP 服务器中的测试过程？

A4: AI 通过实时分析测试结果，提供帮助优化测试用例和提高整体性能的见解，从而改善测试过程。

Q5: 我在哪里可以找到有关 JMeter MCP 服务器的更多信息？

A5: 更多信息可以在官方网站 jmeter.ai 和 GitHub 仓库 QAInsights/jmeter-mcp-server 找到。

🚀 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

📋 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:

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 numpy matplotlib

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