MCP (Model Context Protocol) servers let AI apps access real-time data and external tools, improving accuracy beyond static model knowledge. Choosing between local and remote MCP servers affects security, scalability, and integration. In this article, learn all about these servers and which to choose for your use case.
When you have an application or agent using MCP (model context protocol) servers, one of the architectural decisions you’ll need to take is where exactly they should be located.
Why use MCP servers?
Large language models (LLMs) are trained on vast amounts of data but don’t have built-in access to live, up-to-date