TL;DR By default, Claude has no real-time access to your business data, so any response it gives about your metrics is either a refusal or a confident guess based on pattern recognition. There are four ways to connect business data to Claude (CSV uploads, automation platforms, custom MCP servers, and pre-built MCP). Only the MCP-based options return verified query results, and only a pre-built analytics MCP like Databox delivers that without requiring engineering work. Databox MCP links to Claude in about a minute via Settings → Connectors using OAuth, and the Databox MCP server runs actual queries on your data and returns computed metrics, not LLM estimates. Once connected, Claude effectively becomes a true analytics interface where you can ask ad-hoc business questions, perform threshold checks, and run cross-channel queries across 130+ data sources in natural language. Your data remains secure because Claude does not store or train on individual conversations, and Databox keeps data access under your control. Introduction You ask Claude for last month’s MRR. The reply appears quickly, looks polished, sounds authoritative—and is completely off. Not because Claude is malfunctioning, but because it’s forced to guess. Out of the box, Claude has no direct connection to your business systems. It can’t query your CRM, read from your ad accounts, or inspect your billing platform. So when a marketing manager asks for their numbers, Claude will either decline to answer or produce a believable number based on patterns from its training data. There are four ways to solve this: manual CSV uploads, automation platforms,…