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BigQuery MCP

Query your BigQuery data warehouse using natural language with the Coupler.io MCP server. No SQL knowledge required - just ask AI to extract data, transform, visualize, and generate insights.

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Why to use the BigQuery MCP

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Use case 1

Query sales performance across multiple channels by asking AI to analyze revenue trends, conversion rates, and customer acquisition costs from your warehouse data.

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Use case 2

Generate executive dashboards by requesting AI to pull key business metrics, growth indicators, and performance comparisons from your BigQuery data warehouse automatically.

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Use case 3

Analyze customer behavior patterns by having AI examine user journeys, retention rates, and segmentation data stored across your BigQuery analytics tables.

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Use case 4

Monitor operational metrics by asking AI to track system performance, error rates, and usage statistics from your application and infrastructure data.

What data you can get with the BigQuery MCP

  • Analytics and web data
    Website traffic, user behavior, conversion funnels, session data
  • Sales and revenue data
    Transaction records, customer purchases, revenue tracking, pipeline metrics
  • Customer data
    User profiles, demographics, behavior patterns, lifetime value calculations
  • Marketing data
    Campaign performance, attribution analysis, ad spend, ROI metrics
  • Product usage data
    Feature adoption, user engagement, retention analysis, performance metrics
  • Financial data
    Revenue reports, cost analysis, budget tracking, financial KPIs
  • Operational data
    System logs, performance metrics, error tracking, infrastructure monitoring
  • Inventory and supply chain
    Stock levels, order fulfillment, supplier data, logistics tracking
  • HR and workforce data
    Employee metrics, productivity data, organizational analytics
  • Custom business data
    Industry-specific metrics, proprietary datasets, integrated third-party data

How does MCP work?

1

Step #1

Set up a data flow in Coupler.io by connecting your BigQuery.

2

Step #2

Proceed to the MCP Server page in Coupler.io and follow the instructions there

3

Step #3

Ask AI about your BigQuery - get insights, reports, trends, or charts just by typing your question.

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Set up the MCP server in 5 minutes by following the instructions in the platform or by watching the video

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Frequently asked questions
The Coupler.io MCP (Model Context Protocol) server functions as a connector that links your external data warehouses with AI assistants. It allows AI models like Claude to directly access, query, and analyze your BigQuery data through conversational interactions. Rather than writing complex SQL queries or building custom dashboards, you can simply ask your AI assistant questions about your warehouse data and receive immediate insights, calculations, visualizations, and comprehensive analysis.
The MCP server supports any data source available through Coupler.io's extensive integration library. With more than 70 available connectors, you can integrate BigQuery alongside Google Analytics, Salesforce, HubSpot, Facebook Ads, Shopify, Microsoft Excel, Google Sheets, Pipedrive, Airtable, Xero, QuickBooks, and numerous other platforms. This comprehensive list grows regularly as new data source integrations become available.
No technical skills or complex query languages are needed to interact with your data. The setup process is designed to be user-friendly with simple configuration steps. You need to be on at least the Professional plan and have data flows configured in Coupler.io. You can then talk to your data naturally without needing to learn SQL or complex technical skills.
Security is ensured through multiple layers of protection. The system uses unique personal access tokens that only you can generate through the Coupler.io web application. No external parties can access your data unless you explicitly share your token. The AI receives aggregated data summaries rather than individual records, and your data is never used for AI model training purposes. Coupler.io implements comprehensive security measures protecting your shared information and data transfers from breaches, unauthorized access, and disclosure threats. Your data ownership and privacy remain completely protected.
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