Docker now supports remote Model Context Protocol (MCP) servers, allowing developers to connect easily to external apps like Notion and Linear without manual configuration. With built-in OAuth, users can securely authorize connections in just two commands, streamlining workflows and enhancing productivity.

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.

This article outlines a series of ten hands-on labs focused on Model Context Protocol (MCP) vulnerabilities, each based on real-world exploits. It provides both vulnerable and secure implementations, allowing users to reproduce attacks and understand mitigation strategies in a practical setting. Comprehensive instructions and proof captures accompany each challenge.

Model Context Protocol (MCP) enhances the interaction between AI agents and external tools, but it introduces significant security risks, such as command injection flaws and misconfigurations. Developers must adopt new security practices that focus on policy over traditional static analysis, utilizing Docker's solutions to mitigate risks while maintaining agile workflows.

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.

Mike Coleman from Docker discusses the importance of control over AI tooling deployment in enterprise environments. He provides a detailed guide on how to build a custom Model Context Protocol (MCP) catalog, which includes forking Docker’s official MCP catalog, hosting server images in a private registry, and using the MCP Gateway to connect clients to the curated servers.

The article discusses the challenges developers face when building and using tools with the Model Context Protocol (MCP), including issues related to runtime management, security, discoverability, and trust. It highlights how Docker can serve as a reliable MCP runtime, offering a centralized gateway for dynamic tool management, along with features to securely handle sensitive data. The introduction of the Docker MCP Catalog aims to simplify the discovery and distribution of MCP tools for developers and authors alike.

Docker has launched the MCP Catalog and Toolkit in Beta, aimed at improving the developer experience for Model Context Protocols (MCPs) by streamlining discovery, installation, and security. This initiative involves collaboration with major tech partners and enhances the ease of integrating MCP tools into AI applications through secure, containerized environments.

The article discusses how to integrate Claude Desktop with Docker MCP Toolkit to enhance AI capabilities for developers, enabling Claude to perform real-world tasks like deploying containers and managing repositories securely. It outlines the setup process and demonstrates how Claude can automate tasks that traditionally take hours, significantly improving efficiency and safety through a containerized environment.