This article details the creation of a Go-based gateway designed to securely connect Large Language Models (LLMs) with PostgreSQL databases. The gateway employs the Model Context Protocol (MCP) to prevent sensitive data schema information from leaking to the LLM. It achieves this by dynamically reflecting the database schema and hardening analytical egress, ensuring the LLM only receives pre-approved aggregations rather than raw data or structural details. This approach aims to enable AI adoption in sensitive sectors by mitigating intellectual property risks associated with direct database access. AI
IMPACT Enables secure integration of LLMs with sensitive databases, potentially accelerating AI adoption in regulated industries.
RANK_REASON Article describes a technical implementation for a specific software integration pattern.
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