Understanding MCP: A Practical Guide for Enterprise AI

MCP Explained: Best Practices for Enterprise AI As enterprises scale AI initiatives, securely connecting models, tools, and systems quickly becomes complex. Model Context Protocol (MCP) provides a standardized approach for AI systems to interact with enterprise data, tools, and services. Understanding how MCP works in practice is key to getting real value from it. In this session, we break down MCP fundamentals, including key differences between local and remote MCP, best practices for implementation, and how to leverage MCP with Dataiku, The Universal AI Platform™, to power and manage enterprise-grade AI workflows. You’ll learn how MCP enables scalable, secure integrations, which design choices matter most, and how to apply MCP effectively in real-world environments through concrete use cases. To explore more about Dataiku, check out the rest of our content: CHECK OUT DATAIKU: https://bit.ly/36XBlpK AI&Us: https://www.dataiku.com/stories/ai-an... ROAI: https://www.dataiku.com/return-on-ai/ LinkedIn: https://bit.ly/3lXyRMb X: @dataiku Instagram: @dataiku