What is MBQL support?

MBQL (Metabase Query Language) is a structured JSON-based format that allows Claude to perform aggregations, filters, and breakouts without writing raw SQL code.

Can I run standard SQL queries?

Yes, the skill supports native SQL queries using the BigQuery SQL dialect (Standard SQL) through the METABASE_POST_API_DATASET tool.

How do I find my database or table IDs?

You can use METABASE_GET_API_DATABASE to list databases and METABASE_GET_API_DATABASE_ID_METADATA to retrieve all table and field IDs for a specific database.

Does this skill require a direct BigQuery API key?

No, it accesses BigQuery through a Metabase instance. You connect via the RUBE_MANAGE_CONNECTIONS tool using the Metabase toolkit.

Google BigQuery Automation

Name: Google BigQuery Automation
Author: Tako3832

byTako3832

0•

Gestión de Bases de Datos

Automates Google BigQuery workflows through Metabase integration to execute SQL queries, explore schemas, and perform data analysis.

This skill empowers Claude to interact directly with Google BigQuery data warehouses via the Rube MCP and Metabase integration. It enables automated data exploration, complex SQL execution, and structured query building using Metabase Query Language (MBQL). It is specifically designed for developers and data analysts who need to retrieve real-time insights, verify database schemas, or automate reporting tasks directly within their Claude Code environment without manual context switching.

Características Principales

01Discover and list all connected Metabase data sources and databases

02Execute native BigQuery SQL queries directly from the command line

03Build structured MBQL queries with built-in aggregations and filters

04Explore database schemas, tables, and field metadata in real-time

050 GitHub stars

06Convert structured queries into raw SQL for transparency and debugging

Casos de Uso

01Validating database schemas and exploring table structures during development

02Automated reporting and data extraction for business intelligence tasks

03Performing ad-hoc data analysis using natural language translated into SQL

Características Principales

01Discover and list all connected Metabase data sources and databases

02Execute native BigQuery SQL queries directly from the command line

03Build structured MBQL queries with built-in aggregations and filters

04Explore database schemas, tables, and field metadata in real-time

050 GitHub stars

06Convert structured queries into raw SQL for transparency and debugging

Casos de Uso

01Validating database schemas and exploring table structures during development

02Automated reporting and data extraction for business intelligence tasks

03Performing ad-hoc data analysis using natural language translated into SQL