Context-aware test generation through MCP
Connect sources such as Figma, Jira, GitHub, OpenAPI, and Claude Design so Text2Test can generate test cases from the product artifacts you already use.
Text2Test
Freemium
Text2Testは、デザイン、コード、チケット、仕様書から構造化されたテストケースを生成し、Webテスト自動化ワークフローでテスト計画として実行できるAIネイティブなソフトウェアテストプラットフォームです。
Text2Testとは？
Text2Test generates structured test cases from sources such as designs, tickets, code, and API specs, then runs them as executable plans. Its workflow is centered on MCP connections that let the product read product artifacts and build tests from that context rather than from a prompt alone.
It is aimed at teams that want to automate web testing without writing code for every case. The platform supports plain-text test creation, AI-driven Autopilot steps, script injection, visual checks, and HTTP requests in the same test case, so a single plan can cover UI actions, API assertions, and more dynamic flows.
Text2Testでできること
Five sequence types in one test case
Combine T2T Native, T2T Autopilot, Script Injection, Visual Verification, and HTTP Request steps inside a single sequence when one approach is not enough.
Plan-based execution across run modes
Group test cases into plans and run them on demand, on a schedule, in parallel, or from CI/CD workflows.
Drillable failure reporting
Inspect failed runs at the per-test and per-step level, with inline error snippets and support for screenshots and video.
Plain-text test creation with deterministic output
Write test intent in plain language and have it compiled into deterministic steps, reducing the need for selectors or scripting in routine cases.
Reusable data and API building blocks
Use uploaded CSV, XLS, JSON, or XML data sources, save HTTP requests for reuse, and iterate suites once per row where needed.
利用シーン
“Generate a first test suite from product artifacts”
A team can connect design, issue-tracking, code, and spec sources, then use Text2Test to create an initial structured suite tied back to those inputs.
“Run regression coverage on every push”
Teams shipping frequently can bundle tests into plans and trigger them from CI so failures surface as part of the normal delivery flow.
“Test flows that combine UI and API steps”
When a workflow needs both browser actions and endpoint checks, one test case can mix HTTP requests, visual checks, scripts, and plain-text steps.
“Handle branching or state-dependent flows with Autopilot”
For tickets, checkout paths, or other flows that change based on screen state or data, Autopilot can reason through the next step instead of following a fixed script.
“Review failures and create handoff items”
When a plan run fails, teams can inspect the exact broken step, review the trace, and open a Jira ticket from the failure details.
よくある質問
How does Text2Test create test cases?
It connects to product sources through MCP and generates structured test cases from artifacts such as designs, Jira tickets, GitHub code, and OpenAPI specs.
Do I need to write code to use it?
Routine test creation is described as plain-text based, and the site says no coding is required for the core workflow. Script Injection is available when a specific scripted step is needed.
Can one test case include different kinds of steps?
Yes. The product says a single test case can combine plain text, Autopilot, script injection, visual verification, and HTTP requests.
How are tests run?
Tests are bundled into plans that can be run on demand, on a schedule, in parallel, or from CI/CD integrations.
What happens when a run fails?
Failed runs surface the exact step that broke, with inline error snippets and drillable results; the site also shows screenshots and video as part of the failure view.
クイック情報
- Category
- AI-native software testing
- Primary platform
- Web test automation
- Source connection method
- MCP
- Common source inputs
- Figma, Jira, GitHub, OpenAPI
- Pricing
- Paid plans with Starter, Grow, Pro, and Custom tiers
- HQ
- Delaware, US
Text2Test のトラフィック分析
トラフィックデータは参考情報としてご利用ください。
- ドメイン評価
- 3
Text2Testの代替品
QAgent
qagent.in
QAgent is an AI agent testing and quality assurance platform for developers and agile teams. It connects to an agent through a webhook or endpoint, runs automated test cases, and evaluates responses for groundedness, policy adherence, prompt compliance, and related quality dimensions.
DeepEval
deepeval.com
DeepEval is an open-source LLM evaluation framework for testing and benchmarking AI applications. It helps developers run pytest-native evaluations, score outputs and agent traces, and iterate on systems across text, image, audio, and voice workflows.
Rainforest QA
rainforestqa.com
SaaSチームとCI/CDに対応するノーコードAIテスト自動化
mabl
mabl.com
Web、モバイル、AIアプリ、API向けのエージェント型テスト自動化
Testim
testim.io
Record application flows, add checks and run end-to-end tests. Testim combines AI-assisted element locators with visual test editing and team workflows for web, mobile and Salesforce testing.
MagicPod
magicpod.com
AI-assisted, no-code test automation for web and mobile app QA teams.