This article explains how to use Model Context Protocol (MCP) servers to connect tools and services with language models through Docker. It outlines three integration approaches, highlighting the benefits and challenges of each, from simple setups to complex custom applications.

The Model Context Protocol (MCP) addresses the challenges developers face when integrating AI with external tools by providing a standardized way for large language models to interact securely with APIs. Docker's new MCP Catalog and Toolkit streamline this process, offering a centralized repository of verified MCP servers that enhance developer experience and security. With powerful search capabilities and one-click setup, Docker facilitates easier access to AI developer tools tailored for various use cases.