Natural language SQL at enterprise scale with centralized governance
A Fortune 500 company deployed AI agents that allow non-technical business users to query Teradata and BigQuery data warehouses using natural language, while IT maintains centralized governance for 50+ AI applications through a single MCP server gateway.
The Problem
Business analysts spent days waiting for data team support to write SQL queries. The 'holy grail' of natural language-to-SQL consistently failed because AI models guessed table names and column schemas, producing broken queries 60%+ of the time. Governance was a nightmare: 50+ different AI tools each needed database credentials and permissions.
How MCPFlow Solved It
IT deployed a single, governed MCP server for their Teradata data warehouse and Google BigQuery. The server exposes the ground-truth schema to AI agents, enabling them to write correct SQL on first try. An intelligent query wrapper inspects results for prompt injection attacks and malicious commands hidden in returned data. All 50+ AI applications connect through this one gateway, which enforces row-level security, query timeouts, and audit logging.
MCP Stack Used:
Measurable Outcomes
Query accuracy jumped from 40% to 90%, eliminating the 'guess and retry' problem. Business users gained self-service analytics, reducing data team ticket volume by 70%. IT simplified governance from managing 50 different database connections to securing one MCP server, with complete auditability and rollback capabilities for all AI-generated queries.
Key Metrics:
Our business analysts finally have the self-service analytics they've wanted for years. And our CISO finally has the centralized control they need.
Dr. Rebecca Lawson
VP of Data & Analytics, Global Manufacturing Corp
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