The MCP Server Trap: Why Connectors Don't Equal Good Data

Most developers evaluate MCP servers by implementation ease—what actually matters is the data foundation beneath them. Poor data quality causes cascade failures downstream: rate limits during live sessions, stale fundamentals, silent incompleteness, and undisclosed pricing tiers. This comparison shifts focus from connector evaluation to the critical factors that determine real-world reliability and scalability in financial AI workflows.