# Text2Test 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. - Findings24: - Website: - Pricing: Freemium - Categories: AI Testing Assistant ## What is Text2Test? 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. ## What can Text2Test do? ### 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. ### 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. ## Use Cases ### 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. ## Frequently Asked Questions ### 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. ## Quick Facts - **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