There is a good chance you might have heard the term Model Context Protocol, or MCP, in the context of AI systems recently. But we’re finding that many developers haven’t had the time to learn about what it does or how it fits into agentic workflows. This blog post provides an introduction into what MCP is and how it can be useful. Briefly, the Model Context Protocol (MCP) , introduced in 2024, is a standardized, open source way for large language models (LLMs) to access external tools, providing AI applications with an ecosystem to support the LLM. These tools include databases, programs on the user's computer, APIs of cloud providers, etc. Such support is critical for enabling agentic AI. Hundreds of tools are already accessible via MCP. MCP servers provide standardized support to LLMs At a basic level, LLMs interface via natural language rather than programmatic APIs — LLMs are provided instructions in text and return responses also in text. This is obvious with chatbots, but it is also true in general.…