Systems | Development | Analytics | API | Testing

Analyzing performance test results has long been one of the most complex and time‑consuming aspects of performance engineering. As the volume of testing increases and delivery cycles continue to accelerate, teams face mounting challenges in making sense of vast amounts of data.

You’ve likely heard a lot about MCP (Model Context Protocol) lately. It’s one of the many AI functions that are being added into the testing landscape every day. The open-source standard for connecting AI applications to external systems has been getting significant buzz in enterprise software testing, with Tricentis leading the way with its industry-first secure remote MCP servers.

Autonomous agents — AI-driven bots, virtual assistants, and task-specific automators — are quickly becoming part of everyday business operations. They promise speed, efficiency, and the ability to scale tasks across teams without human intervention. But there’s a new challenge emerging in this AI-driven workplace: AI agent sprawl.

The future of testing is AI-driven, business-oriented, and no-code. Exclusively available for Tosca in the cloud, Tosca’s Model Context Protocol (MCP) Server is a game-changer. It provides a consistent, standardized, and open framework that connects your AI models to Tosca — no need for custom and inflexible API integration. Whether generative, agentic, or any future AI innovation, MCP bridges the gap between AI and QA tools, enabling seamless integration and smarter, faster testing.

At a recent gathering of public sector data leaders, the conversations didn’t revolve around which artificial intelligence tool is fastest or how to adopt zero trust frameworks. They focused on something far more foundational: trust. Specifically: Can we trust our data? At the CDAO Government event, federal and state agency leaders focused on the truth behind effective decision-making and efficient public service delivery: governance only works if the data is complete, accurate, and ready for use.

As modern software delivery processes accelerate, QA teams inevitably feel pressure to maintain quality at scale. SeaLights addresses this challenge by providing deep visibility into test coverage across every stage of the software development lifecycle. It helps teams identify untested code changes, optimize execution, and deliver confidence at release time.