How technical support at Cursor uses Cursor

Cursor's integration into customer support workflows has significantly improved efficiency by consolidating code, logs, team knowledge, and past conversations into a single session, enhancing support engineer throughput by 5–10 times. The process begins with investigating from the codebase using Ask Mode, which allows tracing through product behavior and indexing across multiple repositories within a multi-root workspace. By utilizing MCP servers, support engineers can access comprehensive context from databases, event logs, communication platforms, engineering tickets, and internal documentation, all within Cursor. When issues arise, Datadog MCP provides relevant logs for error analysis, and the integration with Slack and other platforms helps track similar cases. Determining whether an issue is a bug involves cross-referencing with runbooks pulled through Notion MCP, while Linear MCP aids in filing detailed bug reports. Documentation updates are streamlined by tagging Cursor in Slack, prompting cloud agents to update the docs repository. Automation through slash commands, rules, skills, and subagents allows parallel execution of common steps, further improving productivity. This AI-native approach to technical support has enabled a small team to effectively manage a rapidly growing user base by reducing the need to switch between tools and teams.