Anthropic's Model Context Protocol (MCP) is an open standard designed to standardize how artificial intelligence (AI) models interact with various data sources, enabling secure, two-way communication between AI systems and these external resources. MCP acts like a universal connection point, facilitating integrations similar to how USB-C ports work for devices. This protocol allows for the integration of tools and automation of workflows, providing a framework for applications to easily connect to databases, APIs, and local data sources [1][2][3][5][6].

MCP follows a client-server architecture, where 'MCP Hosts' are applications like Claude Desktop or IDEs that want to access data, while 'MCP Servers' expose specific functionalities through the protocol. This structure allows for efficient data retrieval and interaction, enhancing the capabilities of large language models (LLMs) beyond their standalone functions [2][6]. 

Key benefits of MCP include a growing list of pre-built integrations, flexibility in switching LLM providers, and best practices for securing data. It simplifies the development process by eliminating the need for separate connectors for each data source, fostering a more manageable and scalable AI ecosystem [1][3][4].

Introducing the Model Context Protocol

What is Anthropic's model context protocol?

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