AI Agents and MCP in Enterprise Workflows
The proliferation of Large Language Models (LLMs) has opened the door to a new paradigm of intelligent applications: AI agents . These agents, capable of independent reasoning and action, promise to automate complex, multi-step tasks across disparate systems. However, a significant gap remains between building a functional prototype and deploying a secure, reliable, and production-ready agent. This is where the Model Context Protocol (MCP) 1 , an open standard developed by Anthropic, becomes crucial. MCP provides a standardized way for LLMs to securely and reliably interact with external tools, APIs, and data sources. This article examines a specific use case presented by the company Gentoro 2 , which leverages MCP to bridge the chasm between an unstructured "firehose" of user communications and structured, automated business workflows. The Enterprise Problem and the MCP Solution A common challenge for businesses is the fragmentation of communication and data. The talk hig...
