https://step.dev/knowledgebase/31/categories/ai/ Recent content in AI on Step Documentation Hugo -- gohugo.io en Tue, 20 Oct 2026 00:00:00 +0000 https://step.dev/knowledgebase/31/ai/step-agent/getting-started/ Tue, 29 Sep 2026 00:00:00 +0000 https://step.dev/knowledgebase/31/ai/step-agent/getting-started/ The Step AI Agent ships as a Step Automation Package. You give it the test cases to produce, and collect a finished and validated package when it completes. You choose how you interact with it. Choose your path The three paths below run the same workflow and produce the same automation package. Work from Execution Best for Step Studio Local A visual UI for defining test cases, launching runs and reading reports, with no command line IDE Local Working in your own toolchain, on your existing code base Step Platform Central Running with nothing installed locally, on shared infrastructure, with agentic and automation results visible to the whole team Before you start Check the CLI version. https://step.dev/knowledgebase/31/ai/step-agent/tutorials/ Tue, 20 Oct 2026 00:00:00 +0000 https://step.dev/knowledgebase/31/ai/step-agent/tutorials/ Two worked end-to-end tutorials take the same scenario — a guest checkout on a storefront — from a plain-language test case to automation running in a pipeline and on a schedule. They differ in where you work and what you own, and each can be followed on its own. Agentic test automation with Step Studio (UI) Choose this if you own the requirement and the journey the business cares about, and you would rather not write code or selectors. https://step.dev/knowledgebase/31/ai/mcp-server/ Mon, 29 Jun 2026 00:00:00 +0000 https://step.dev/knowledgebase/31/ai/mcp-server/ The Step MCP Server lets AI assistants and coding agents drive the Step automation platform through the Model Context Protocol (MCP). https://step.dev/knowledgebase/31/ai/mcp-server/getting-started/ Mon, 08 Jun 2026 00:00:00 +0000 https://step.dev/knowledgebase/31/ai/mcp-server/getting-started/ Overview The Step MCP Server lets AI assistants and coding agents (such as Claude Code, Claude Desktop, and Cursor) drive the Step automation platform through the Model Context Protocol (MCP). It brings AI-powered software testing into your existing automation workflows: agents can author, run, and analyse test executions on Step without leaving their environment. Instead of clicking through the UI, you can triage a failed run (even a load test with thousands of failures) by asking in plain language and getting a cited root-cause summary back. https://step.dev/knowledgebase/31/ai/step-agent/configuration/ Tue, 06 Oct 2026 00:00:00 +0000 https://step.dev/knowledgebase/31/ai/step-agent/configuration/ Reference for everything a run accepts. For a first run, Getting started covers the two required parameters and a minimal example. Execution parameters Parameter Required Meaning instructions yes The test cases to produce and what each must cover. apDirectory yes Where the finished package is published. If a package is already there, it is extended rather than replaced. stepApiKey for central runs API key for the Step instance the generated package is executed against. https://step.dev/knowledgebase/31/ai/mcp-server/multi-profile-config/ Mon, 29 Jun 2026 00:00:00 +0000 https://step.dev/knowledgebase/31/ai/mcp-server/multi-profile-config/ The Step MCP Server supports a YAML-based configuration file that lets you define multiple profiles — each targeting a different Step instance or project. This is the recommended approach when you work with more than one Step instance, or manage many projects on the same instance. For the simple single-instance setup using environment variables, see Getting Started. Key concepts: profiles and projects A profile is a connection identity: a Step instance URL, an API token, and an optional default project. https://step.dev/knowledgebase/31/ai/step-agent/data-privacy/ Tue, 29 Sep 2026 00:00:00 +0000 https://step.dev/knowledgebase/31/ai/step-agent/data-privacy/ The Step AI Agent calls a large language model (LLM) as part of producing automation packages. Content from the application under test therefore reaches a model by design. This page states what does, what does not, and what you decide. Unlike the Step MCP Server, which never calls a model itself and leaves that choice to your own AI assistant, the agent makes those calls within its workflow. What leaves your environment While producing automation, the agent sends to the model: https://step.dev/knowledgebase/31/ai/step-agent/ Tue, 29 Sep 2026 00:00:00 +0000 https://step.dev/knowledgebase/31/ai/step-agent/ Overview The Step AI Agent is an autonomous AI agent that turns high-level requirements or test specifications into validated and executable Step Automation Packages: standardized, reusable and scalable automation artefacts that can be used and reused across: Functional Testing Load & Performance Testing Synthetic Monitoring Robotic Process Automation (RPA) Give it the systems under test (SUTs) in scope, your requirements, and any existing test cases or code. From there it runs transparently and unattended: the agent analyses what already exists, plans and implements the required automation, executes and validates it, and uses execution feedback to repair (self-healing) and stabilise the result before handover. https://step.dev/knowledgebase/31/ai/mcp-server/tools/ Mon, 29 Jun 2026 00:00:00 +0000 https://step.dev/knowledgebase/31/ai/mcp-server/tools/ Reference for all tools exposed by the Step MCP Server. For setup and installation, see Getting Started. All tools accept two optional shared parameters: profile (which Step instance and credentials to use) and project (which project to act on). The discovery tools below are the exception: they don’t require a project. When omitted, parameters fall back to the configured defaults (see Profile and project resolution). Every tool’s response includes a resolvedContext block reporting the profile, baseUrl, and project actually used. https://step.dev/knowledgebase/31/ai/ Wed, 03 Jun 2026 11:00:00 +0200 https://step.dev/knowledgebase/31/ai/ The core principle of Step is to bring teams and technologies onto a single, scalable platform and unify software automation disciplines: Functional testing Load and performance testing Synthetic monitoring Robotic process automation (RPA) The Step AI ecosystem brings greater autonomy across the testing and automation lifecycle through a set of AI-powered technologies, workflows and capabilities designed to reduce effort while improving the quality of automation outcomes. It can be adopted at different levels of autonomy, from exposing individual Step capabilities to your AI assistant with the Step MCP to delegating complete automation workflows to the Step AI Agent.