QualityMax MCP

AI-native test automation for web apps.

От сообщества: Добавлен пользователем или импортирован; проверьте владельца перед подключениемРаботаетБез входаГлобальныйБесплатноМожет изменять данные

Что умеет

  • Import Repository: Import and analyze a GitHub repository for testing. Creates a default project if none specified.
  • Generate Tests: Generate Playwright tests for a specific feature or component
  • Run Tests: Execute Playwright tests or verified generated Appium mobile flows and return a compact per-script summary (status, duration, failure reason, next action). Managed mobile runs are asynchron

Какие данные видит

Нужен ли аккаунт

Не нужен: сервер работает без входа

AI-native test automation for web apps. Create and manage projects, test cases, automation scripts, test runs, and QualityMax workflows through secure OAuth.

Как подключить

Как подключить QualityMax MCP к Claude

Адрес сервера, который нужно вставить в настройках Claude:

https://qualitymax-mcp--qualitymax.run.tools

  1. Откройте Claude (сайт claude.ai или приложение для компьютера).
  2. Перейдите в Настройки → Коннекторы (в английском интерфейсе: Settings → Connectors).
  3. Нажмите Добавить пользовательский коннектор (Add custom connector).
  4. Вставьте адрес сервера, скопированный ниже, в поле URL удалённого MCP-сервера и нажмите Добавить.
  5. В чате нажмите + → Коннекторы и включите новый коннектор.

Пользовательские коннекторы доступны на тарифах Free, Pro, Max, Team и Enterprise. На Free можно добавить только один. В Team и Enterprise коннектор сначала добавляет владелец организации в Настройки организации → Коннекторы.

Авторизация

После нажатия Добавить откроется окно входа в сервис. Войдите под своим аккаунтом и подтвердите доступ. Пароль Claude не видит.

Как подключить QualityMax MCP к ChatGPT

Адрес сервера, который нужно вставить в настройках ChatGPT:

https://qualitymax-mcp--qualitymax.run.tools

  1. Откройте ChatGPT в браузере (chatgpt.com). Нужен тариф Plus, Pro, Business, Enterprise или Edu.
  2. Один раз включите режим разработчика: Настройки → Приложения → Дополнительные настройки → Режим разработчика (Settings → Apps → Advanced settings → Developer mode).
  3. Откройте Настройки → Коннекторы и нажмите Создать (Create).
  4. Заполните форму: Название (любое), Описание (одна фраза, что делает сервис), URL MCP-сервера (скопируйте ниже).
  5. В поле Аутентификация выберите OAuth, если сервис требует вход, иначе Нет. Нажмите Создать.
  6. В новом чате откройте + → Приложения/Коннекторы и включите коннектор.

Название раздела у OpenAI менялось (Connectors → Apps/Plugins). Если пункт называется иначе, ищите «режим разработчика» в настройках. В рабочих пространствах Business/Enterprise администратор должен разрешить пользовательские коннекторы.

Авторизация

При первом использовании ChatGPT откроет окно входа в сервис. Войдите и подтвердите доступ.

Как подключить QualityMax MCP к Cursor

Адрес сервера, который нужно вставить в настройках Cursor:

https://qualitymax-mcp--qualitymax.run.tools

Быстрый способ: нажмите кнопку Открыть в Cursor ниже, Cursor сам предложит добавить сервер.

Вручную:

  1. В Cursor откройте Settings → Cursor Settings → MCP и нажмите Add new global MCP server.
  2. Вставьте JSON, скопированный ниже, в открывшийся файл ~/.cursor/mcp.json (для одного проекта: .cursor/mcp.json в корне проекта).
  3. Сохраните файл. Сервер появится в списке MCP; при необходимости пройдите авторизацию по кнопке рядом с ним.

Авторизация

Если сервис требует вход, рядом с сервером в списке MCP появится кнопка авторизации.

Список инструментов сервера (60)

Технические названия из tools/list. Нужны только разработчикам.

import_repositoryImport and analyze a GitHub repository for testing. Creates a default project if none specified.
generate_testsGenerate Playwright tests for a specific feature or component
run_testsExecute Playwright tests or verified generated Appium mobile flows and return a compact per-script summary (status, duration, failure reason, next action). Managed mobile runs are asynchronous; poll get_execution using the returned execution_id. Full stdout/stderr, traces, and artifact paths are opt-in — request them only when the compact failure is not enough to act on.
apply_patch_and_runPatch an automation script and immediately re-run it, returning one compact result. Use this instead of update_script followed by run_tests: it collapses the fix-and-verify loop into a single round trip.
analyze_coverageAnalyze test coverage and identify gaps in the repository
generate_area_planRun deep gap analysis on a repository to discover and map testing areas.
generate_tests_for_areasGenerate test cases for specific discovered test areas.
get_discovery_graphReturn the repository's evidence-grounded discovery graph: a lineage of repository → evidence → test areas → test cases → automation scripts, with grounding status and confidence per node. Use to audit test coverage lineage.
ai_reviewPerform AI-powered code review and suggest improvements
get_review_preferencesGet the user's AI code-review preferences (which categories to check, which to skip). Returns effective preferences: per-repo overrides merged over global defaults. Call without repository_id for global defaults.
set_review_preferencesSet or update AI code-review preferences. Controls which categories the reviewer checks (security, performance, test_coverage, type_safety, accessibility, style, secrets_scanning, ai_safety_for_agents) and an optional custom_focus string. Use scope='global' for defaults that apply everywhere, or scope='repo' with a repository_id for per-repo overrides.
create_prCreate a pull request with generated tests or fixes
whoamiReturn identity of the user owning the current API token: user_id, email, username, full_name, role, tier, and a count of accessible projects. Use this first when debugging 'Access denied' errors to confirm which account the token belongs to.
list_projectsList projects for the current user, including each project's vanity URL slug and project type (web or native_mobile). ALWAYS call this before creating a new project to check if a similar project already exists.
create_projectCreate a new project (optionally with main_url). Will check for similar existing projects and ask for confirmation if found.
update_projectUpdate an existing project (e.g., set main_url for AI crawl)
get_project_memoryReturn compact durable memory from prior MCP agent negotiations, project learnings, and verified test runs. Call this before generating or repairing tests for an existing project; then call get_script only for the most relevant verified script to keep context and cost low.
get_repositoryGet repository details and stored analysis
refresh_repositoryRefresh an existing repository analysis at its latest commit. Private repositories reuse the stored GitHub App connection.
list_repositoriesList repositories for a project
repo_qualityGet the imported repository's stored quality signal without starting a new scan.
repo_coverageGet the imported repository's stored coverage signal without starting a new scan.
list_test_casesList test cases for a project
create_test_caseCreate a test case in a project. If no steps are provided, detailed steps are auto-generated from the title/description (disable with auto_generate_steps=false).
import_test_cases_from_documentImport test cases from document text content. The AI will analyze the text and extract test cases automatically.
import_from_testrailImport test cases from TestRail into a project (requires saved TestRail credentials)
start_ai_crawlStart an AI crawl job for a project (requires project.main_url unless url is provided)
start_ai_crawl_from_test_caseStart an AI crawl job using an existing test case as instructions. IMPORTANT: This tool will first generate a virtual test plan that MUST be approved by the user before proceeding. You must present the plan to the user, wait for their approval, then call this tool again with the approved_virtual_test_plan parameter to proceed with the crawl.
check_ai_crawl_statusCheck the status of an AI crawl job. Use this to see if a crawl has completed and inform the user when tests are ready.
start_mobile_auditStart a detailed Mobile Readiness Audit for a project. It captures responsive evidence at 1440px, 768px, and 375px, checks console/link/accessibility/layout risks, and prepares a shareable report. Uses the project main_url unless url is provided.
get_mobile_audit_statusGet status, score, and report path for a Mobile Readiness Audit.
list_mobile_auditsList Mobile Readiness Audits for a project, newest first.
share_mobile_auditCreate or return the public share link for a completed Mobile Readiness Audit.
parse_mobile_audit_reportConvert extracted text from a QualityMax-style mobile audit PDF or HTML report into structured findings: ID, severity, surface, breakpoints, root cause, and fix prompt. Use the result to create or link follow-up work; this tool never changes project data.
get_mobile_audit_evidenceReturn the screenshot URLs and bounded scanner evidence for a completed Mobile Readiness Audit. Use this before Claude writes a qualitative report.
render_mobile_audit_reportStore a structured BYO-Claude mobile-audit report and render a shareable HTML report plus a downloadable PDF. This does not call a QualityMax model.
import_document_and_crawlComplete workflow: Import document/text, create test cases, generate virtual test plan for approval, then initiate AI crawl. IMPORTANT: This tool will first generate a virtual test plan that MUST be approved by the user before proceeding. You must present the plan to the user, wait for their approval, then call this tool again with the approved_virtual_test_plan parameter to proceed with the crawl.
show_available_commandsList all available commands and tools that the assistant can use. Use this when the user asks 'what can you do?' or 'list your capabilities'.
get_project_summaryGet a summary of a project including counts of test cases, scripts, and executions. Use this when the user asks 'what's in my project?' or 'show me project stats'.
get_test_caseGet detailed information about a specific test case including its description, steps, and related automation scripts. Pass `if_version_matches` to skip the body when nothing changed, and `fields` to fetch only what you need.
get_scriptGet an automation script's details including the generated Playwright/Cypress test code. Pass `if_version_matches` with the version from a previous read to get a cheap `not_modified` answer, and `fields` to fetch only what you need.
list_scriptsList automation scripts for a project or test case. Returns script names and IDs (use get_script to view the code).
get_executionGet a test execution's status, timing, and outcome. Log entries and artifact paths are counted by default and returned only when explicitly requested.
search_test_casesSearch for test cases by title, description, or tags. Better than listing all test cases when looking for something specific.
query_dataQuery data from the system using flexible queries. Use this for exploratory queries or when you need to list data with filters. For specific single-item lookups, prefer specialized tools like get_test_case, get_execution, etc.
parse_qtmlParse a QTML (Quality Testing Meta Language) source string and return its structured representation as JSON. Use this to inspect the contents of a QTML document.
validate_qtmlValidate a QTML source string. Returns whether it is valid and any errors found.
export_project_as_qtmlExport a QualityMax project and its test cases as a QTML document string.
import_qtmlImport a QTML source string into QualityMax, creating a project and/or test cases from the QTML contract and intents.
convert_qtml_to_playwrightImport a QTML source string and then trigger AI Playwright code generation for each imported test case.
test_deployed_environmentTest a deployed environment end-to-end. Discovers the UI, generates a Playwright test, and executes it. The run is ephemeral unless project_id is provided, in which case a linked test case, script, and result are saved. Returns pass/fail with test code and screenshots.
get_ai_crawl_resultsGet the results of a completed AI crawl job including generated test scripts, test cases, and flow memory.
generate_gap_testsGenerate test cases to fill coverage gaps found by analyze_coverage. Analyzes the repository's deep-scan results and generates E2E, smoke, integration, and security test cases.
generate_code_for_test_caseGenerate automation test code for a specific test case using AI. Supports Playwright, pytest, Cypress, Selenium, Vitest, Jest, Kotlin, Scala, Go (`go test`), and Rust (`cargo test`). When `framework` is omitted, the framework is auto-resolved from project settings, linked-repository language detection, and the test category.
check_generation_statusCheck a background code-generation job started by generate_code_for_test_case (personal Codex / Claude Code seat routes return a job_id instead of code, because a seat run takes minutes). Poll about every 30s. A seat runs one job at a time, so wait for a terminal status ('completed', 'failed', or 'timed_out') before generating the next test case rather than starting several in parallel.
update_test_caseUpdate an existing test case's fields (title, description, steps, expected result, category, priority).
delete_test_caseDelete a test case. Requires ownership of the parent project.
delete_projectDelete a project. Requires ownership. This will also delete all associated test cases, scripts, and executions.
update_scriptUpdate an automation script's name or code. Prefer `patch` over `code`: it sends only the lines you are changing instead of re-uploading the whole script, which is the single largest token saving available on this server.
update_mobile_flowUpdate a managed mobile script from its canonical QTML mobile flow. Validates the flow and platform, rejects stale revisions, increments the revision, and deterministically recompiles the executable script. Use this instead of update_script for managed mobile flows.