LambdaTest MCP Server

LambdaTest 是 TestMu AI

面向智能体测试的 TestMu AI MCP Server

借助 TestMu AI 的 MCP Server，您可以直接在 Cursor、Claude、Copilot 及其他 MCP 客户端中使用自然语言，从 IDE 中运行、调试和分类测试，该服务器为 HyperExecute、自动化、SmartUI 和可访问性工具提供支持。

立即试用发布说明

TestMu AI（原 LambdaTest）内置 MCP Server

使用自然语言，通过 HyperExecute、自动化、可访问性和 SmartUI MCP 工具，从 IDE 中运行、调试和分类测试。

使用 Google 免费开始

HyperExecute MCP 工具自动化 MCP 工具可访问性 MCP 工具SmartUI MCP 工具

使用 HyperExecute MCP 进行测试编排

TestMu AI 的 HyperExecute MCP 免除了手动编写 YAML 和切换仪表板的麻烦。通过自然语言，即可在 IDE 中生成 YAML 配置、运行器命令并监控作业。

探索 HyperExecute MCP

generateHyperExecuteYAML： 为测试项目执行生成 YAML 配置。

answerHyperExecuteQuery： 从 HyperExecute 文档中获取即时答案。

getHyperExecuteJobInfo： 检索给定测试运行的详细作业级信息。

getHyperExecuteJobSessions： 获取与 HyperExecute 作业关联的所有会话详情。

使用自动化 MCP 进行测试失败分类

TestMu AI 的自动化 MCP 通过将 TestID 详情、命令日志、网络日志和控制台错误汇集到一次对话中，加速测试失败分类，以便即时进行根因分析。

探索自动化 MCP

自动化测试详情： 检索特定测试的全面信息。

自动化命令日志： 访问所有 Selenium 命令的执行日志。

自动化网络日志： 分析测试期间的浏览器流量和网络行为。

自动化控制台日志： 查看浏览器控制台输出，包括错误和警告。

upload_app 工具： 上传移动应用以进行测试。

使用可访问性 MCP 进行 WCAG 和 a11y 审计

TestMu AI 的可访问性 MCP 通过返回包含可立即应用的修复指导的详细审计报告，在 WCAG 和 a11y 违规问题进入生产环境之前将其捕获。

探索可访问性 MCP

getAccessibilityReport： 获取任何公开 URL 的可访问性报告。

buildLocalAppForAnalysis： 构建并启动一个本地 React 应用以检测可访问性问题。

analyseAppViaTunnel： 通过 TestMu AI 隧道分析本地应用测试的可访问性失败情况。

使用 SmartUI MCP 进行视觉回归调试

TestMu AI 的 SmartUI MCP 通过直接在 IDE 中用通俗易懂的语言解释像素、布局、DOM 和感知变化，减少了视觉回归调试中的手动差异调查工作。

探索 SmartUI MCP

getSmartUIResources： 获取比较运行的所有视觉资源。

summarizeSmartUIPixelDiff： 识别并解释截图之间的原始像素差异。

summarizeSmartUILayoutDiff： 检测间距、对齐和尺寸相关的布局问题。

summarizeSmartUIDomDiff： 描述 DOM 结构和属性的变化。

analyzeSmartUIHumanDiff： 模拟人类如何感知视觉变化。

analyzeSmartUIRun： 提供跨所有分析层的完整调试摘要。

getSmartUIScreenshotInfo： 检索 SmartUI 截图的元数据和详细信息。

downloadSmartUIDomFiles： 下载 DOM 结构文件以进行深入分析。

AI 智能体质量工程

智能体测试

KaneAI

浏览器测试

真机云

应用自动化

HyperExecute

视觉 UI 测试

可访问性测试

智能体测试

测试聊天机器人、语音助手等 AI 智能体。

更多关于智能体测试

自主测试

从合成最终用户的角度，对被测智能体进行详细分析。

多角色模拟

模拟国际来电者、数字新手等多种用户角色。

风险评分与回归

对被测智能体进行端到端回归测试并提供洞察。

KaneAI by TestMu AI

使用自然语言规划、编写和演进端到端测试。

自然语言

通过简单描述来编写测试，无需脚本，无需代码，只需通俗易懂的语言。

测试场景生成

从文本、JIRA 工单、PRD、图像和电子表格生成结构化测试用例。

测试编写

使用 KaneAI 为您的桌面和移动设备上的网站及 Web 应用编写浏览器测试。

浏览器测试

在 3000 多种浏览器-操作系统-设备组合上快速验证您的网站。

响应式测试

检查您的网站在桌面、平板和移动设备上不同视口下的呈现效果。

DevTools 调试

使用预装的 Chrome 和 Safari DevTools 调试跨浏览器问题。

地理位置测试

通过不同的地理 IP 测试，确保各地用户都能获得正确的体验。

真机云

在 10000 多台真实设备上测试 Web 和移动应用。

手势测试

测试点击、滚动、缩放、滑动等自然手势。

真实场景

利用 40 多种功能，在真实硬件设备上测试各种边缘情况。

高级调试

在测试会话中直接使用设备日志、网络日志和 UI 检查器进行调试。

应用自动化

在 10000 多台真实移动设备和平板电脑上进行自动化移动应用测试。

并行执行

在数百台真实的 Android 和 iOS 设备上同时运行自动化测试。

框架支持

Appium、XCUITest、Espresso 和 Detox，移动自动化的所有选项。

本地测试

在各种真实的 Android 和 iOS 设备上测试本地和私有托管的应用。

HyperExecute

速度提升高达 70% 的 AI 原生测试编排云。

自愈测试

自动修复测试脚本，减少不稳定性和手动维护。

智能编排

根据历史数据自动重新排序测试运行，更快地暴露失败并缩短反馈时间。

根因分析

通过实时日志分类错误并获取 AI 驱动的纠正性洞察。

视觉 UI 测试

AI 原生视觉测试，可捕获跨浏览器和设备的 UI 回归。

像素比较

检测布局、颜色、字体和元素位置方面的视觉偏差。

设计到开发

将 Figma 设计与实时网页和应用屏幕进行比较，以确保准确性。

智能忽略

通过 AI 原生检测过滤掉不相关的布局变化，减少误报。

可访问性测试

对 Web 和移动应用进行可访问性测试，以实现包容性用户体验。

WCAG 合规性

根据 WCAG、ADA 和 Section 508 标准扫描 Web 和移动应用。

定时扫描

按日、周或月自动执行定期可访问性审计。

屏幕阅读器

在真实设备上测试与屏幕阅读器和辅助工具的兼容性。

播放

TestMu AI（原 LambdaTest）的成功案例

50%

测试执行时间缩短

“HyperExecute 是一个高度可靠的测试执行平台，并且拥有出色的客户支持。”

Sagar Uday Kumar

高级工程经理

Dashlane

Lereta

Dunelm

Trepp

Transavia

预约演示

更多喜爱 TestMu AI（原 LambdaTest）的理由

了解 TestMu AI 如何通过 AI 原生编写、更快的执行速度以及跨 Web、移动和 AI 应用的更深入测试洞察来加速您的测试。

使用 Google 免费开始

TestMu AI 在 2025 年 Gartner® 魔力象限™ 中被评为挑战者

阅读报告

TestMu AI 在《The Forrester Wave™：自主测试平台，2025 年第四季度》中获得认可

阅读报告

荣誉墙

TestMu AI 是全球中小企业和大型企业的首选。

企业级安全

我们通过全球安全、隐私、负责任 AI 和 ESG 标准来保护您的数据和 AI 系统。

集成

在您工作的地方工作，与您团队依赖的工具进行 120 多种集成。

用户

300 万+

测试

15 亿+

企业

1.8 万+

国家

132

媒体报道

常见问题

什么是 MCP Server？

MCP Server 是一个通过模型上下文协议（Model Context Protocol）向 AI 智能体公开工具、资源和提示的程序，该协议是 Anthropic 于 2024 年 11 月推出的一项开放标准。服务器向任何兼容 MCP 的客户端通告其能力，客户端（AI 智能体）在运行时调用这些工具以获取数据或执行模型训练数据之外的操作。

MCP 在软件测试中用于什么？

在软件测试中，MCP 允许 AI 智能体通过自然语言驱动测试工作流：生成配置、执行套件、拉取日志、总结失败以及运行视觉或可访问性检查。智能体无需在 IDE、仪表板和终端之间切换，而是在聊天中内联调用正确的 MCP 工具并返回结果，从而压缩了编排和调试时间。

MCP Server 如何与 AI 智能体协同工作？

客户端（如 Claude Code 或 Cursor 等 AI 智能体）通过 stdio 或 HTTP/SSE 连接到服务器，并请求其能力。服务器返回一个包含 JSON Schema 定义的工具列表。当用户提示智能体时，它会选择相关工具，发送结构化调用，服务器则针对底层系统执行该调用，然后返回模型可以推理的类型化响应。

哪些 AI 客户端支持 MCP Server？

Claude Code、Claude Desktop、Cursor、Windsurf、GitHub Copilot Chat、Cline、Continue、Zed AI 和 JetBrains AI Assistant 目前都支持 MCP Server。任何实现模型上下文协议规范（stdio 或 HTTP/SSE 传输）的客户端都可以连接，这意味着新的 MCP 感知工具无需重写服务器集成即可工作。

如何在 Cursor 或 Claude Code 中设置 MCP Server？

在 Cursor 中，打开设置 → MCP → 添加新 MCP Server，并将其指向服务器的命令或 HTTP 端点。在 Claude Code 中，运行“claude mcp add ”或直接编辑 ~/.claude.json。注册后，智能体会自动发现可用工具，您可以在聊天中调用它们。大多数企业 MCP Server 在工具可调用之前会添加一个 OAuth 步骤。

MCP 和 API 有什么区别？

API 是为代码到代码调用构建的固定端点契约；客户端需要为每个端点和版本更改进行自定义集成。MCP 是为 AI 到工具调用构建的：它标准化了智能体在运行时发现能力、跨调用维护会话状态以及解析类型化响应的方式。当向 MCP Server 添加新工具时，每个连接的智能体都会自动获取，无需重新部署。

MCP Server 可以运行 Selenium、Playwright、Cypress 或 Appium 测试吗？

可以。MCP Server 不会取代您的测试框架；而是对其进行封装。TestMu AI MCP Server 在项目分析期间会检测 Selenium、Playwright、Cypress、Appium、TestNG、JUnit、PyTest、WebdriverIO 及类似框架，然后为您的 AI 智能体生成正确的配置和运行器命令以执行。测试执行仍然在底层云网格上进行。

MCP 如何帮助调试失败的测试？

MCP 服务器可以拉取测试元数据、Selenium 命令日志、浏览器网络活动以及任何失败运行的 console 错误，然后将数据交还给聊天中的 AI 代理。代理根据日志进行推理，关联事件，并提出根本原因，将原本需要在多个选项卡仪表板中查找的工作转变为一次提示即可完成。

模型上下文协议安全吗？

MCP 本身定义的是传输和消息格式，而非身份验证；安全性取决于服务器实现。生产环境服务器通常使用 OAuth 2.1、限定范围的令牌和 TLS 加密传输。企业部署会增加基于角色的权限、审计日志和数据驻留控制，当 MCP 流量携带生产日志或客户数据时，这些措施就变得很重要。

MCP 服务器可以免费使用吗？

该协议是开源且免费的。服务器定价各不相同：许多社区服务器是免费的，而供应商托管的服务器则根据底层平台（使用量、席位或计算资源）计费，而非针对 MCP 层本身。TestMu AI MCP 服务器包含在每个 TestMu AI 账户中，仅消耗团队已付费的测试执行分钟数。

TestMu AI MCP 服务器中包含哪些工具？

服务器中提供了四个 MCP 工具。HyperExecute MCP 处理项目分析、YAML 生成、运行器命令、作业信息和会话详情。Automation MCP 获取测试详情、Selenium 命令日志、网络日志和 console 日志。SmartUI MCP 汇总像素、布局、DOM 和人类感知的视觉差异。Accessibility MCP 对公共 URL、本地 React 构建和隧道应用运行 WCAG 审计。

TestMu AI MCP 服务器支持哪些 AI 助手？

TestMu AI MCP 服务器为 Cursor、Claude Code、Claude Desktop、Claude.ai（Web）、VS Code 中的 GitHub Copilot、Antigravity、OpenAI Codex CLI、Cline 和 Continue 提供了文档化的设置路径。任何其他兼容 MCP 的客户端都可以通过使用 mcp-remote 的通用 STDIO 配置进行连接，因此采用该协议的较新助手无需在服务器端进行更改即可工作。

TestMu AI MCP 服务器使用哪些传输方法？

服务器支持两种传输方式。对于大多数客户端，推荐使用 Streamable HTTP，并使用带有 OAuth 身份验证的端点。对于尚不支持 Streamable HTTP 的客户端，可通过 mcp-remote 使用 STDIO，并在后台使用相同的 OAuth 身份验证端点。

配置后，为什么 MCP 工具没有出现在我的 AI 客户端中？

通常有三个原因。首先，完全退出并重新启动客户端（仅软重载通常不够）。其次，验证 JSON、TOML 或 YAML 配置是否存在语法错误，尤其是尾随逗号和未转义的路径。第三，对于像 Continue 这样的客户端，请确认您处于代理模式而非聊天模式。如果 OAuth 已完成但工具仍未出现，请从客户端的 MCP 设置中重新进行身份验证。

查看更多问题

TestMu AI（前身为 LambdaTest）/MCP 服务器

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STDIO is available through mcp-remote for clients that don't yet support Streamable HTTP, and uses the same OAuth-authenticated endpoint behind the scenes."}},{"@type":"Question","name":"Why aren't MCP tools showing up in my AI client after configuration?","acceptedAnswer":{"@type":"Answer","text":"Three things usually cause this. First, fully quit and relaunch the client (a soft reload often isn't enough). Second, validate the JSON, TOML, or YAML config for syntax errors, especially trailing commas and unescaped paths. Third, for clients like Continue, confirm you are in Agent Mode rather than Chat Mode. If OAuth completed but tools still don't appear, re-authenticate from the client's MCP settings."}}]}
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