In the realm of software development, the manual process of identifying and resolving critical issues through error logs is a time-consuming challenge that can be optimized with AI agents. These agents, which rely on comprehensive context and real production data, can streamline the task of diagnosing root causes and suggesting fixes for top issues. By integrating real-time error monitoring tools like Rollbar with development environments such as VS Code, and connecting them through an MCP (Model Context Protocol) server, engineers can automate the retrieval and analysis of error data. This setup allows AI agents to access full stack traces and relevant data, enabling more efficient root cause analysis and code modification suggestions. Consequently, the time required for engineers to address issues is significantly reduced, providing a more effective and rapid troubleshooting process.