Systems | Development | Analytics | API | Testing

Your SmartBear Zephyr test data holds the answers you need before you ship: what’s covered, what passed, where the risk sits. That data has always lived one context switch away, behind the Jira UI. The SmartBear MCP Server changes that. It brings your Zephyr test data into any MCP-compatible AI client, so quality keeps pace with how fast your team builds. This guide covers where testing sits in the AI age, what MCP is, and how it unifies data visibility within your Zephyr workflow.

Four years ago, we started Multiplayer with an ambitious goal: to help teams work better on distributed systems. Since then we've grown to thousands of users, and we reached a milestone I'm especially proud of: open-sourcing our AI debugging agent to put it in the hands of every developer who's ever wrestled with a gnarly bug or waded through PR slop from AI tools. Today I'm excited to share the next chapter: Multiplayer is joining FilingRamp.

Two AI features can cost the same to build and land on opposite sides of the P&L. Add a chatbot to a listing page, and you get a support-deflection number that plateaus in a quarter. Rework search ranking so a buyer who types “quiet street, near a school, room for an office” gets the right ten homes instead of 400 filtered results, and you move search-to-contact conversion, which sits at the top of every revenue metric downstream.

Generating synthetic data is one thing. Trusting it is another. As enterprises adopt synthetic data for development and testing, important questions quickly emerge: Can it be reproduced consistently? Does it accurately reflect real-world business scenarios? In fact, our survey of enterprise leaders found that “consistent, high-quality test data to reduce defects” was their priority in test data automation at 43%.

Discover a Bug Reporting Blueprint with 15 essential templates for QA Testing Workflow in 2023. Boost efficiency and streamline your software testing!

When npm announced that version 12 would require developers to explicitly approve install scripts, the reaction across the community was almost universally positive. For years, security researchers had warned that package installation had become one of the weakest links in the JavaScript supply chain. Every npm install represented an opportunity for third-party code to execute automatically, often before developers had even looked at the source they were downloading.

Sometimes, comments are not specifically contextual to an element, but rather to your entire webpage. This is why we launched floating comments!

Choosing an enterprise test management platform is an architecture decision, not just a feature checklist. That choice comes down to how the platform stores data, how deeply testing connects to development, how far reporting and traceability extend, and how much the platform can absorb as testing volume, automation, and compliance requirements grow.

The swift introduction of Large Language Models (LLMs) and autonomous agents to business software ecosystems has posed a fundamental security issue: the unification of code and data. Traditional software designs carefully separate user input from operational commands. LLMs, on the other hand, are fed system commands, retrieved documents, user communications, and third-party API answers all in one context window.