Systems | Development | Analytics | API | Testing

DreamFactory 7.7.0 is now the recommended stable release. It's a substantial one: AI agents become governed, human-owned API consumers; a new open-source API Builder lets you author custom REST endpoints without writing scripts; versioned Schema Contracts catch database drift before it reaches your consumers; and the platform baseline moves to Laravel 13.25 and PHP 8.3.

A BigQuery MCP server lets AI agents like Claude query your Google BigQuery data through a standard protocol instead of ad-hoc integrations. Because BigQuery bills by bytes scanned, an unconstrained agent is not just a security risk but a budget risk: one careless full-table scan on a wide table costs real money. This guide covers what a BigQuery MCP server does, the three ways to set one up, and the cost and security controls that matter before you let an agent anywhere near your analytics data.

Every utility is being pulled in two directions. Operations, engineering, and customer-facing teams all want data in modern applications: outage maps, field-service apps, asset-health dashboards, regulator reporting, and increasingly AI assistants that can answer questions about generation, load, or maintenance history. At the same time, the security team's job is to make sure none of that convenience becomes a path into systems that open spillway gates, trip breakers, or control pressure.