Your B2B customers want to see their data. Usage metrics, billing summaries, conversion funnels, performance dashboards. Every customer expects analytics inside your product. They shouldn't have to ask your support team for a CSV export.
The question isn't whether to ship customer-facing analytics. It's how.
Most teams start with one of two approaches. They embed a BI tool (Metabase, Looker, Power BI) and fight with multi-tenancy, iframe styling, and paid embedding licenses. Or they build custom charts from scratch and spend months maintaining SQL queries, API endpoints, and frontend components that nobody asked for.
Both approaches burn engineering time on the wrong problem. You end up building analytics infrastructure instead of your product.
And there's a surface most of these tools miss entirely: the AI agent. Customers increasingly want to ask questions about their data inside Claude or ChatGPT and get a chart back. That's a different problem from embedding a dashboard, and it's where @bonnard/mcp-charts fits, covered later in this post.
