MCP is a standard that allows
AI models to connect and communicate with external systems, such as databases, tools, or APIs, to obtain real-time information and perform more complex tasks. It's like a bridge between AI and the outside world.
MCP facilitates
AI models interacting with external sources without the need to program specific integrations. For example, a language model can use MCP to query a banking database and answer questions about recent transactions, or connect to a weather API to provide updated forecasts.
This protocol uses a client-server architecture: the model acts as a client and consults the MCP server, which organizes access to the necessary data sources. Unlike other approaches such as
RAG systems, MCP directly accesses information without the need to process and store data in
embeddings, making it faster and more efficient.
MCP is transforming how AIs interact with the real world, allowing them to be more practical and contextually useful. For example, a
AI Assistant could check your calendar, consult real-time traffic, and suggest when to leave to arrive on time for a meeting. This standardization promises to simplify and enhance the use of AI in everyday applications, significantly improving its ability to provide accurate and up-to-date answers.