Get started using the Model Context Protocol to experiment with AI capabilities using Docker Desktop.
ai/ml
Meet Gordon: An AI Agent for Docker
We share our experiments creating a Docker AI Agent, named Gordon, which can help new users learn about our tools and products and help power users get things done faster.
Unlocking Efficiency with Docker for AI and Cloud-Native Development
Learn how Docker helps you deliver secure, efficient applications by providing consistent environments and building on best practices that let you discover and resolve issues earlier in the software development life cycle (SDLC).
The Model Context Protocol: Simplifying Building AI apps with Anthropic Claude Desktop and Docker
Discover how the Model Context Protocol (MCP) simplifies building AI applications by seamlessly integrating Anthropic Claude with Docker Desktop, enhancing developer productivity and workflow efficiency.
Docker Desktop 4.37: AI Catalog and Command-Line Efficiency
Docker Desktop 4.37 streamlines AI-driven development with the new AI Catalog integration, command-line management capabilities, upgraded components, and enhanced stability to empower modern developers.
Docker 2024 Highlights: Innovations in AI, Security, and Empowering Development Teams
We look at Docker’s 2024 milestones and innovations in security, AI, and more, as well as how we helped teams build, test, and deploy more easily and quickly than ever.
How to Create and Use an AI Git Agent
We show how to create Git agent and use this Git agent to understand PR branches for a variety of user personas — without needing to know the ins and outs of Git.
How AI Assistants Can Decode GitHub Repos for UI Writers
Exploring AI-assisted tools for UI writers, we demonstrate how to enhance GitHub PR review workflows to identify user-facing text changes, and offer a step-by-step guide and insights into leveraging LLMs effectively.
Extending the Interaction Between AI Agents and Editors
We explore the interaction of AI agents and editors by mixing tool definitions with prompts using a simple Markdown-based canvas.