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 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.