MCP servers: why you need to know about them and how they work
About
MCP have revolutionized the way AI connects to resources. Standard API approaches required the developer to customize each connection. With MCP servers, a standardized protocol replaces these fragmented API connections with a single, universal connection method. MCP servers enable the researcher to connect to multiple data sources simultaneously, create reproducible data pipelines, get the most out of agentic AI, and build large libraries that can be quickly and easily queried/summarized.
Speaker
Jeff Hastings
Jeff Hastings is a PhD student in the Faculty of Computing & Data Sciences at Boston University, advised by Dr. Joshua Peterson. He earned a BA and MA in Political Science from Utah State University, followed by an MS in Computational Social Science from the University of California, San Diego. His research applies machine learning, deep learning, and reinforcement learning to better understand, explain, and improve human, artificial, and agentic decision-making. Prior to his PhD, he worked as an AI Data Scientist at Thermo Fisher Scientific.