ContextQA Documentation

ContextQA documentation — complete reference for AI-powered test automation, the MCP server, integrations, and platform administration.

Quick answer

ContextQA documentation — complete reference for AI-powered test automation, the MCP server, integrations, and platform administration. Use this page to choose the relevant workflow guide, understand the available capabilities, and navigate to the supporting instructions.

What this page covers

ContextQA is an AI-powered test automation platform that creates, executes, and maintains browser, mobile, API, and Salesforce tests without requiring test code. The AI agent interprets natural language test steps, locates UI elements using visual AI and DOM analysis, and self-heals broken tests when an application changes.

ContextQA: An AI-powered test automation platform for creating and executing application tests in natural language. Review the results and available screenshots, recordings, and logs for each run to decide whether the required behavior was verified.

Evaluate one workflow against your acceptance criteria. Book a Demo → — Bring a testing requirement and review the workflow, evidence, and ownership boundaries.

---

What ContextQA Does

ContextQA executes every test through an AI pipeline that handles navigation, element interaction, evidence capture, and self-healing automatically. Tests run on real browsers — Chromium, Firefox, and WebKit.

Key capabilities:

• AI test generation — create test cases from a URL, Jira ticket, Figma design, OpenAPI spec, video recording, or plain-text requirements
• Natural language execution — steps written in plain English execute as full browser interactions
• Self-healing — when a UI element moves or changes, the AI finds the new location automatically
• MCP server — discoverable tools for AI agents (Claude, Cursor, VS Code Copilot) to create, execute, and analyze tests programmatically
• 17 plugin integrations + 5 CI/CD guides — plugins such as Jira, Slack, Microsoft Teams, Azure DevOps, Linear, and Trello, plus CI/CD guides for GitHub Actions, Jenkins, and GitLab CI

---

Start by Role

🧪 Tester

Write tests in plain English, run on real browsers, get video evidence. No code required.

→ ContextQA for Testers

⚙️ SDET

Manifest-discovered MCP tools, Playwright export, CI/CD API, and full evidence access.

→ ContextQA for SDETs

📋 QA Manager

Test plans, analytics dashboard, flaky detection, shareable reports. Release confidence, quantified.

→ ContextQA for QA Managers

💻 Developer

Generate tests from Jira tickets, PR quality gates, AI root cause in your terminal.

→ ContextQA for Developers

🗺️ PM

Turn your acceptance criteria into automated tests. Track feature coverage. Know before you ship.

→ ContextQA for Product Managers

🏗️ Eng Manager

Parallel CI gates, SSO, team metrics, and AI that eliminates test maintenance toil.

→ ContextQA for Engineering Managers

🚀 VP/CTO

The ROI, build-vs-buy analysis, and enterprise architecture for AI test automation at scale.

→ ContextQA for VPs & CTOs

---

Documentation Sections

Getting Started

New to ContextQA? Start here. Covers the platform overview, first-test workflow, an optional portfolio lab, core concepts, and the AI pipeline architecture.

• Introduction to ContextQA
• Complete Product & Workflow Guide
• Self-Serve Workspace Onboarding
• Quickstart Guide
• AI Testing Portfolio Lab
• Core Concepts
• Platform Architecture

Business Use Cases

Start with the business risk: requirements-to-test traceability, complex authenticated web flows, risk-based regression, document and KYC application validation, Salesforce lifecycles, or connected delivery workflows. Each guide maps capabilities to an implementation pattern, evidence, guardrails, and success measures.

Migrate to ContextQA

Move an existing automation portfolio without losing intent or coverage. Start with the source-neutral planning checklist, then use the Playwright, Selenium, Tricentis Tosca, or mabl guide for source-specific mapping, validation, parallel running, cutover, and rollback.

• Migration Planning & Acceptance Checklist
• Playwright Migration
• Selenium Migration
• Tricentis Tosca Migration
• mabl Migration

Evaluation & Governance

Run an evidence-led evaluation instead of comparing feature checklists. Use copyable pilot scorecards, PR evidence records, agent-skill validation, browser-grid migration controls, CI negative-path tests, change-impact ledgers, and clean-environment portability checks to make an adopt, revise, extend, or stop decision.

Web Testing

Create and run automated tests for web applications. Covers test case authoring, the step editor, test suites, data management, and self-healing.

Mobile Testing

Automate iOS and Android app testing. Covers device setup, app uploads, gesture authoring, and multi-device test plans.

API Testing

Test REST APIs with assertions and request chaining. Covers request configuration, response validation, and multi-step API flows.

Salesforce Testing

Automate Salesforce Lightning UI testing. Covers AI-assisted test generation, metadata-aware execution, and parallel test plans.

Execution

Run tests manually, on a schedule, or from CI/CD. Covers parallel execution, environments, scheduling, and evidence capture.

Reporting

Analyze test results and diagnose failures. Covers execution reports, the analytics dashboard, AI root cause analysis, and flaky test detection.

AI Features

The AI capabilities that power ContextQA. Covers test generation sources, the autonomous agent pipeline, knowledge bases, and custom agents.

Integrations

Connect ContextQA to your existing toolchain. Covers Jira, Slack, GitHub Actions, Jenkins, GitLab CI, CircleCI, Azure DevOps, and webhooks. ContextQA offers 17 portal integrations (configured from Integrations & Plugins) across bug tracking, project management, notifications, and infrastructure, plus 5 CI/CD integration guides that trigger test plans from your pipeline.

MCP Server

Use ContextQA from AI agents via the Model Context Protocol. Covers installation, authentication, manifest-based tool discovery, troubleshooting, and agent workflow patterns.

Administration

Manage users, roles, SSO, and workspace settings.

Reference

Glossary, changelog, and keyboard shortcuts.

Planning & Decision Guides

Make buyer and operating decisions with reusable evidence artifacts. Compare vendors on one workflow, calculate cost per usable release verdict, choose a service or platform ownership model, request security evidence, design the smallest operable stack, assess team skills, validate model-routing controls, and turn industry claims into bounded experiments.

Testing with AI Coding Agents

Write and verify tests with Claude Code, Cursor, Codex, Copilot, Gemini CLI, or Windsurf. Start with generic unit, integration, functional, and end-to-end workflows; then connect ContextQA MCP for managed application testing. Follow the Playwright example, compare framework choices, and validate exports before using them in CI.

• Choose a coding-agent testing guide
• Write Playwright tests with an AI agent
• Export ContextQA tests and verify portability

---

Quick Links

I want to…	Go to
Match ContextQA features to a business problem	Business Use Cases
Share one guide to the full product and its workflows	Complete Product & Workflow Guide
Create my first test	Quickstart Guide
Set up a new self-serve workspace	Self-Serve Workspace Onboarding
Migrate an existing test portfolio	Migration Overview
Run an evidence-led ContextQA evaluation	Evaluation & Governance
Validate a reusable QA agent skill	QA Agent Skill Validation
Generate a test from a Jira ticket	AI Test Generation
Upload an Android APK or iOS IPA build	Uploading Apps
Chain API calls and reuse response data	API Chaining
Find execution video, screenshots, logs, and traces	Video & Screenshots
Investigate repeated or intermittent failures	Flaky Test Detection
Run tests in a CI/CD pipeline	GitHub Actions or Jenkins
Use ContextQA from Claude or Cursor	MCP Server Overview
Fix an MCP connection, OAuth, or manifest problem	MCP Connection Troubleshooting
Give an AI agent the ContextQA documentation	Use the Docs with Search and AI
Understand why a test failed	Failure Analysis
Create roles and assign least-privilege access	Roles & Permissions
Review plan, credits, and usage	Billing & Usage
Set up the platform for my team	Administration
Look up a tool in the MCP API	Tool Reference
Understand what "self-healing" means	AI Self-Healing
Write unit, integration, functional, or end-to-end tests with an AI coding agent	Testing with AI Coding Agents
Compare vendors, architecture, cost, security, or operating models	Planning & Decision Guides

---

Platform Requirements

Requirement	Detail
Supported browsers	Chromium, Firefox, WebKit (Safari)
Mobile platforms	iOS 14+, Android (API level 21+)
MCP server Python version	3.9+
MCP server default port	8080
Deployment options	Local (uv), Docker, Google Cloud Run

---

Common questions about ContextQA

What is ContextQA?

ContextQA is an AI-powered test automation platform for creating, executing, and maintaining web, mobile, API, and Salesforce tests. Teams can describe workflows in natural language, import requirements, or record an interaction, then review the generated test and its execution evidence.

Do I need to write code to use ContextQA?

No code is required for the standard test-creation and execution workflow. Testers can use natural-language instructions, recording, or supported imports. Developers and SDETs can still add custom JavaScript, API steps, CI/CD automation, or MCP-based agent workflows when they need more control.

What applications can ContextQA test?

ContextQA supports browser applications, Android and iOS apps, REST APIs, Salesforce, and documented enterprise workflows. Start with the web, mobile, API, or Salesforce guide for target-specific prerequisites.

How does ContextQA reduce test maintenance?

Natural-language steps describe user intent instead of exposing brittle selector code. During web execution, self-healing can identify an equivalent element after routine UI drift and persist the repaired element reference when the match is sufficiently reliable. Genuine product failures still remain failures for investigation.

Can ContextQA run tests from CI/CD or an AI coding agent?

Yes. Teams can prepare test-plan quality gates for supported CI/CD systems, and authenticated MCP-compatible agents can use ContextQA tools to create tests, trigger executions, poll status, and retrieve results. See Integrations and the MCP Server.

Can search engines and AI tools read this documentation?

Yes. The public documentation provides crawlable HTML, a sitemap, an AI-oriented llms.txt index, and Markdown versions of individual pages. See Use the Docs with Search and AI for the public endpoints and retrieval examples.

---

Need Help?

• Search these docs using the search bar above
• Check the Glossary for term definitions
• Not sure where to start? Browse by Role
• If a page is unclear or out of date, use the page-rating control at the bottom and include the heading or step that needs attention

---

Want a guided tour? Book a Demo → — Our team will walk through ContextQA with your actual application and testing goals. Most teams are running their first tests within 24 hours of the demo.