A Model Context Protocol (MCP) server that provides secure, read-only access to BigQuery datasets, allowing LLMs to query and analyze data through a standardized interface.
https://github.com/ergut/mcp-bigquery-serverStop writing SQL queries. Start having conversations with your data.
The BigQuery MCP Server bridges the gap between your AI assistant and your BigQuery datasets, letting you ask questions like "What were our top customers last month?" and get instant, accurate results. No more switching between Claude and the BigQuery console, no more wrestling with complex JOIN syntax, no more waiting for that one SQL expert on your team.
Skip the SQL Translation Layer Instead of translating business questions into SQL, then interpreting results back to insights, you now have direct conversations with your data. Ask follow-up questions, dive deeper into trends, and explore hypotheses without writing a single query.
Secure by Design Read-only access with built-in query limits (1GB processing cap) means you can explore freely without worrying about accidentally running expensive operations or affecting production data. Your service account permissions stay minimal.
Zero Context Switching Stay in Claude Desktop while accessing all your BigQuery datasets. No more jumping between applications, copying results, or losing your train of thought mid-analysis.
Customer Success Analysis "Which customers had the highest churn rate last quarter, and what were their usage patterns before churning?" Get the full analysis with charts and insights, not just raw query results.
Product Performance Deep Dives "Show me user engagement metrics for our new feature launch, broken down by user segment and week." Follow up with "What about compared to our previous feature launches?" without starting over.
Operational Monitoring "Any unusual patterns in our error logs this week?" Then immediately ask "What's the geographical distribution of these errors?" to drill down into root causes.
Financial Reporting "Generate our monthly revenue report with year-over-year comparisons" becomes a single request instead of multiple complex queries and manual data manipulation.
The fastest setup uses Smithery's auto-installer:
npx @smithery/cli install @ergut/mcp-bigquery-server --client claude
Enter your Google Cloud project ID, and you're analyzing data in under two minutes. For manual setup or custom configurations, you have full control over authentication methods (Cloud CLI or service account keys) and query parameters.
This isn't a proof-of-concept. With 91 GitHub stars and active development, it's being used by teams who need reliable data access. The server handles both tables and materialized views, includes proper schema exploration, and maintains the security boundaries your data team requires.
Perfect for data teams who spend too much time writing queries instead of finding insights, product managers who need quick answers without bothering analysts, and anyone who believes conversations with data should feel as natural as conversations with colleagues.
The BigQuery MCP Server turns your AI assistant into a data analyst that knows your business, understands your schema, and never gets tired of answering follow-up questions.