AI Test Case Generation with MCP Server: Example Prompts and Setup
Updated August 2026: setup for Claude Code, Claude Desktop, Cursor, Windsurf, and Codex, plus 17 MCP tools and example prompts for AI test case generation.
Insights, tutorials, and updates on software testing and QA
Updated August 2026: setup for Claude Code, Claude Desktop, Cursor, Windsurf, and Codex, plus 17 MCP tools and example prompts for AI test case generation.
Updated August 2026: what harness engineering means for QA, plus the six reusable primitives every agent harness shares and a five-level maturity model.
Updated August 2026: learn how data-driven testing works in TestCollab - test parameters, reusable test datasets, and one test case across many data rows.
Release management best practices change when AI writes the code. Twelve behaviors that keep change failure rate down as merge volume climbs on your team.
Compare 10 AI test case generation tools for requirements, Jira, screenshots, APIs, and UI automation. See verified features, pricing, and best use cases.
Updated August 2026: hands-on comparison of 10 AI testing tools - TestCollab, Katalon, Testim, Applitools, Mabl, TestMu AI. Verified pricing, AI agent product lines, and where agentic testing fits.
Side-by-side comparison of the 10 best test management tools in 2026 - pricing, Jira integration, AI features, and honest pros/cons. Includes free and open-source options.
Migrate Azure Test Plans, suites, test cases, steps, tags, and metadata into TestCollab with a guided import that keeps your test structure organized.
TestCollab autonomous QA agents are here. Explore focused agents for regression, security, accessibility, performance, compliance, code, SEO, and more.
Entra ID SSO and SCIM provisioning for TestCollab Enterprise plans: Microsoft sign-in, group-to-role mapping, and automatic joiner and leaver handling.
On June 13, 2026, a US order cut foreign access to Claude Fable 5. For QA teams running AI agents, it is a lesson in model risk: the new vendor lock-in.
ISTQB CT-AI v2.0 split AI testing in two and rebuilt it for the LLM era. Here's what the new standard for testing AI systems requires, and how QA teams run it.