The Coralogix MCP Server now integrates Real User Monitoring (RUM) data with MCP-compatible AI coding assistants like Claude, Cursor, and Windsurf. This allows developers to query live frontend performance data, JavaScript errors, Web Vitals, and network failures using natural language during incidents. The integration creates a closed-loop debugging workflow: RUM identifies the issue, the AI correlates it to codebase context, and developers can go from error detection to a pull request fix within a single conversation. The post walks through common incident scenarios including error triage, network failure investigation, performance regression analysis, and mobile debugging, all using conversational prompts instead of manual dashboard navigation.
Table of contents
The 2 AM problem: you have data, but the workflow is fragmentedWhat changed: your AI assistant can query Real user monitoringStart where incidents start: impact-ranked error triageFollow the trail: network failures and “it’s not really a frontend bug”Performance regressions: Web vitals without the deep diveWhat users actually did: turning RUM into investigation-grade behavior contextMobile is not a special caseGetting startedSort: