Spur

Overview and fit

Compatibility

Test languages

Natural language

Target operating systems

iOS Android

Device modes

Responsive viewport

What it tests

Product kind

AI testing agent, Testing platform

Testing types

End-to-end, Functional, Regression, Smoke, Exploratory

Targets

Web app, Native mobile

Use cases

Pull request validation, Regression testing, Release gating, Cross platform testing, Test generation

Classification lists positively established capabilities. Absence from a list does not mean lack of support.

Creation and execution

Authoring methods

Natural language, AI-generated workflow, Imported tests

Execution models

Hybrid

Deployment

SaaS

License

Proprietary

Capabilities

Maintenance, reliability, and debugging

Setup difficulty

Low

Maintenance approaches

Self-healing, Managed service

Maximum concurrency

null

Debug artifacts

Screenshot, Video, Console log, Network log

Reliability mechanisms

Auto wait

Interfaces

Web UI, MCP

Pricing

Security and deployment

Certifications

undefined

Data regions

Unknown

Data retention

Unknown

Customer data used for training

Unknown

Support

Channels

Slack, Docs, Email

Support SLA

Unknown

Related pages

• AI Testing Tools
• Testing Tools with GitHub Integrations
• Top 24 AI Testing Tools for Developers
• Top 6 AI Testing Tools for Product Managers
• Top 21 AI Testing Tools for Natural Language
• Top 20 AI Testing Tools for iOS
• Top 20 AI Testing Tools for Android
• Top 13 AI Testing Tools for Responsive Viewports
• Spur alternatives

Sources and verification

1. 1Spur | AI QA Testing & Test Automation · Official website · Spur · retrieved 2026-09-26

   Supports 67 claims, high confidence · verified 2026-09-26

   • Adapts to UI changes
   • AI executes the app
   • AI generates code only
   • Audience
   • Audit logs
   • Authoring method
   • Autonomous exploration
   • Browser extension testing
   • Certifications
   • CI execution
   • Code authoring
   • Company size
   • Configurable retention
   • Cross-platform testing
   • Customer data used for training
   • Data regions
   • Data residency
   • Debug artifacts
   • Deployment
   • Execution model
   • Free tier
   • GitHub PR checks
   • Languages
   • License
   • License identifiers
   • Local execution
   • Maintenance approach
   • Max concurrency
   • Merge gating
   • Native desktop testing
   • Native mobile testing
   • Natural language authoring
   • OAuth testing
   • On-premises deployment
   • Parallel execution
   • Parameterized tests
   • Pricing
   • Pricing models
   • Private network access
   • Private runners
   • Product kind
   • Product status
   • RBAC
   • Real device testing
   • Recorder
   • Runner OS
   • SCIM
   • Secrets management
   • Selector-free execution
   • Setup difficulty
   • SSO (OIDC)
   • SSO (SAML)
   • Summary
   • Support channels
   • Support SLA
   • Target OS
   • Targets
   • Test import
   • Testing types
   • Tool
   • Training opt-out
   • Trial
   • Use cases
   • Uses AI
   • Vendor
   • Video recording
   • Vision-based interaction

   How does pricing work?: Annual plans based on test-run volume - not per seat, so your whole team (QA, PMs, engineers) can use Spur.

   Does Spur test native mobile apps?: Tests are written once in natural language and run across web, iOS, and Android. | Can we import our existing test cases?: Yes - Spur imports from test management tools (e.g., qTest, Zephyr) and converts cases to runnable tests in minutes.

   Is Spur SOC 2 compliant?: Yes, Spur is SOC 2 Type 2 compliant.

   Tests are written in natural language.

   Customers with real applications: Enterprises that work with Spur, ship at the speed of generation

   How is our data handled?: Configurable data retention and deletion policies, continuous vulnerability scanning and pen-testing, 99.9% uptime with multi-region redundancy.

   Context from where work lives.: Logs, network, screenshots. | How do you prevent false positives?: Every run produces full video playback and step-level evidence, so you can see exactly what the agent saw.

   Does Spur need access to our codebase?: No. Spur tests from the outside, like a real user. You provide a URL (and a build file for native apps).

   How is Spur different from Selenium, Playwright, or record-and-play tools?: Spur's agents execute intent - "add a medium black legging to cart and check out" - so tests survive redesigns, A/B tests, and daily merchandising changes.

   How does pricing work?: Book a demo for a quote tailored to your release cadence.

   Does Spur test native mobile apps?: Tests are written once in natural language and run across web, iOS, and Android.

   Who maintains tests when our site changes?: Mostly no one - intent-based tests adapt. When something does need updating, it's a plain-English edit, and our team helps.

   How does pricing work?: Plans include parallel execution and support.

   How does pricing work?: Annual plans based on test-run volume - not per seat, so your whole team (QA, PMs, engineers) can use Spur. Plans include parallel execution and support. Book a demo for a quote tailored to your release cadence.

   title: Spur | AI QA Testing & Test Automation

   Contrasts itself with record-and-play tools.

   title: Spur | AI QA Testing & Test Automation | Does Spur test native mobile apps?: Yes - iOS and Android, using your build file. Tests are written once in natural language and run across web, iOS, and Android.

   What kind of support do you offer?: Every customer gets a dedicated Slack Connect channel with our team. Plans include unlimited test-creation support, and higher tiers include full test management. | Where can I find documentation and guides?: You can follow step‑by‑step guides in our docs to write your first tests | FAQ: Did we miss a question? Email us directly

   How is our data handled?: 99.9% uptime with multi-region redundancy.

   Does Spur test native mobile apps?: Yes - iOS and Android, using your build file.

   Does Spur test native mobile apps?: Yes - iOS and Android, using your build file. Tests are written once in natural language and run across web, iOS, and Android.

   Does Spur test native mobile apps?: Yes - iOS and Android, using your build file. Tests are written once in natural language and run across web, iOS, and Android. | Functional Testing: Functional Testing | Exploratory Testing: Exploratory Testing

   Which CI/CD tools do you support?: You can run Spur tests as part of your GitHub workflows (for example, on each pull request) and use status checks to block merges when tests fail

   Not explicitly stated if it uses vision or DOM.

2. 2Manual Runs - Spur Documentation · Official docs · Spur · retrieved 2026-09-26

   Supports 10 claims · Vendor documented, high confidence · verified 2026-09-26

   • Automatic retries
   • Browser engines
   • Browsers
   • Cross-browser testing
   • Device modes
   • Headed execution
   • Headless execution
   • Network mocking
   • Secrets injection
   • Test sharding

   Browsers (web tests): Browsers (web tests)

   Viewports (web tests): Viewports (web tests)

3. 3Scenario Tables - Spur Documentation · Official docs · Spur · retrieved 2026-09-26

   Supports 1 claim · verified 2026-09-26

   • Reusable steps
4. 4AI Test Generation - Spur Documentation · Official docs · Spur · retrieved 2026-09-26

   Supports 3 claims · verified 2026-09-26

   • AI test generation
   • Test data generation
   • Uses AI
5. 5Spur AI - Spur Documentation · Official docs · Spur · retrieved 2026-09-26

   Supports 3 claims · verified 2026-09-26

   • AI failure analysis
   • Self-healing
   • Uses AI
6. 6Spur MCP Integration - Spur Documentation · Official docs · Spur · retrieved 2026-09-26

   Supports 2 claims · Vendor documented, high confidence · verified 2026-09-26

   • Interfaces
   • MCP server

   Spur MCP Integration: Spur MCP Integration

7. 7MCP Setup - Spur Documentation · Official docs · Spur · retrieved 2026-09-26

   Supports 3 claims · verified 2026-09-26

   • MCP server
   • SDK
   • VS Code extension

   Uses MCP via GitHub Copilot in VS Code, not a dedicated extension.

8. 8Integrations Overview - Spur Documentation · Official docs · Spur · retrieved 2026-09-26

   Supports 1 claim · Vendor documented, high confidence · verified 2026-09-26

   • Integrations

   Issue Tracking & Bug Reporting: Jira | Issue Tracking & Bug Reporting: Linear | Issue Tracking & Bug Reporting: Azure DevOps | Communication & Notifications: Slack | Development Workflows: GitHub | Development Workflows: GitLab

9. 9GitHub - Spur Documentation · Official docs · Spur · retrieved 2026-09-26

   Supports 1 claim · verified 2026-09-26

   • GitHub
10. 10GitHub Agent - Spur Documentation · Official docs · Spur · retrieved 2026-09-26

    Supports 3 claims · verified 2026-09-26

    • Autonomous PR validation
    • PR comments
    • PR-aware test selection
11. 11Override URLs - Spur Documentation · Official docs · Spur · retrieved 2026-09-26

    Supports 1 claim · verified 2026-09-26

    • Preview deployment testing
12. 12GitLab - Spur Documentation · Official docs · Spur · retrieved 2026-09-26

    Supports 1 claim · verified 2026-09-26

    • Scheduled execution
13. 13Web Prompting Guide - Spur Documentation · Official docs · Spur · retrieved 2026-09-26

    Supports 17 claims · verified 2026-09-26

    • Accessibility checks
    • API assertions
    • Canvas testing
    • Dark and light mode testing
    • Database assertions
    • Email testing
    • File download testing
    • File upload testing
    • iframe testing
    • Multi-tab testing
    • Notification testing
    • PDF validation
    • Performance measurement
    • Semantic visual assertions
    • Spelling and grammar checks
    • Video content validation
    • Visual regression
14. 14Mobile Prompting Guide - Spur Documentation · Official docs · Spur · retrieved 2026-09-26

    Supports 2 claims · Vendor documented, high confidence · verified 2026-09-26

    • Auto-waiting
    • Reliability mechanisms

    Supported Actions: Wait

15. 15MCP for AI-Powered QA & Test Automation | Spur · Official website · Spur · retrieved 2026-09-26

    Supports 8 claims · Vendor documented, high confidence · verified 2026-09-26

    • Console logs
    • Debug artifacts
    • Execution traces
    • Failure grouping
    • Interactive debugging
    • Network logs
    • Replay
    • Screenshots

    Context from where work lives.: Logs, network, screenshots. | How do you prevent false positives?: Every run produces full video playback and step-level evidence, so you can see exactly what the agent saw.

Hands-on tested: no (documentation research only) · Content updated 2026-09-26