MCP Server for Conversational Analytics in Beverage Manufacturing

The Challenge

In the fast-paced beverage manufacturing sector, real-time insights into production line efficiency, supply chain logistics, and inventory levels are critical. However, this data was siloed across multiple legacy systems.

Factory managers had to rely on specialized data engineering teams to write SQL queries and generate dashboards. This bottleneck meant that by the time insights were delivered, the operational window to act on them had often closed.

Our Approach

To bridge this gap, Widle.ai leveraged the Model Context Protocol (MCP), an open standard that allows Large Language Models (LLMs) to securely and contextually interface with external data sources.

• Developed a custom MCP Server connecting directly to the client's Snowflake data warehouse and production REST APIs.
• Configured strict role-based access control (RBAC) ensuring the LLM only retrieved data the querying user was authorized to see.
• Integrated the MCP Server with a conversational frontend, enabling users to ask complex analytical questions (e.g., 'What was the yield of line B yesterday compared to last month?').
• Implemented real-time data fetching to ensure the LLM responses were grounded in the most current manufacturing data, eliminating hallucinations.

Results & Impact

Widle.ai implemented state-of-the-art computer vision models trained specifically for brand safety and contextual targeting. The pipeline was designed to operate entirely on the edge or in secure enclaves, ensuring data privacy.