How Engineers Are Turning Enterprise Databases into AI Agents Using Azure

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A technical walkthrough published on DEV Community demonstrates how to expose a read-only enterprise system of record to an AI agent using Microsoft Azure services, including Logic Apps, API Management, and Agent Foundry. The architecture uses the Model Context Protocol (MCP) to present backend data as discrete, typed tools that an AI agent can call in plain language, without users needing to know underlying field names or system structure. A single Azure Logic App acts as a dispatcher, routing tool requests through an OAuth-secured connection to the source system while fetching credentials safely from Azure Key Vault. Key design principles include keeping the agent strictly read-only, guarding against prompt-injection risks in free-text fields, and pushing aggregation work down to the source system to minimize data transfer. The guide emphasizes prototyping against real APIs early to catch field-name mismatches, which are identified as the most common silent failure in such integrations.

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