Model Context Protocol (MCP) servers provide a standardized way for language models to interact with various tools, APIs, and services. They act as intermediaries, simplifying the integration process but also introducing challenges, such as runtime issues, secrets management, and the complexity of client-server connections. To address these problems, Docker offers a solution through its MCP Toolkit and Catalog, which streamline the deployment and management of MCP servers using containers. The Docker MCP Toolkit and Catalog allow developers already familiar with Docker to easily spin up MCP servers without needing to manage underlying language runtimes or secrets. The Toolkit acts as a control panel for launching servers and connecting them to existing clients, all while ensuring secure defaults. The MCP Gateway enhances this setup by centralizing routing and authentication, making it easier to manage multiple MCP servers and integrations. For developers looking to build multi-agent applications, Docker's cagent framework provides a YAML-based approach that simplifies orchestration. Users define agent roles and tool access without writing extensive code. For those with advanced needs, traditional agent frameworks like LangGraph or CrewAI offer full control over agent behavior, allowing for complex logic and integration with backend systems. Each approach caters to different levels of complexity and user experience, from beginners to seasoned developers.