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 is an AI-native software testing platform that generates structured test cases from designs, code, tickets, and specs, then runs them as plans in web test automation workflows.
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.
Connect sources such as Figma, Jira, GitHub, OpenAPI, and Claude Design so Text2Test can generate test cases from the product artifacts you already use.
Combine T2T Native, T2T Autopilot, Script Injection, Visual Verification, and HTTP Request steps inside a single sequence when one approach is not enough.
Group test cases into plans and run them on demand, on a schedule, in parallel, or from CI/CD workflows.
Inspect failed runs at the per-test and per-step level, with inline error snippets and support for screenshots and video.
Write test intent in plain language and have it compiled into deterministic steps, reducing the need for selectors or scripting in routine cases.
Use uploaded CSV, XLS, JSON, or XML data sources, save HTTP requests for reuse, and iterate suites once per row where needed.
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.
Teams shipping frequently can bundle tests into plans and trigger them from CI so failures surface as part of the normal delivery flow.
When a workflow needs both browser actions and endpoint checks, one test case can mix HTTP requests, visual checks, scripts, and plain-text steps.
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.
When a plan run fails, teams can inspect the exact broken step, review the trace, and open a Jira ticket from the failure details.
It connects to product sources through MCP and generates structured test cases from artifacts such as designs, Jira tickets, GitHub code, and OpenAPI specs.
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.
Yes. The product says a single test case can combine plain text, Autopilot, script injection, visual verification, and HTTP requests.
Tests are bundled into plans that can be run on demand, on a schedule, in parallel, or from CI/CD integrations.
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.
Traffic data is for reference only.
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