Docker Hub catalogs

Docker Hub catalogs are your go-to collections of trusted, ready-to-use container images and resources, tailored to meet specific development needs. They make it easier to find high-quality, pre-verified content so you can quickly build, deploy, and manage your applications with confidence. Catalogs in Docker Hub:

• Simplify content discovery: Organized and curated content makes it easy to discover tools and resources tailored to your specific domain or technology.
• Reduce complexity: Trusted resources, vetted by Docker and its partners, ensure security, reliability, and adherence to best practices.
• Accelerate development: Quickly integrate advanced capabilities into your applications without the hassle of extensive research or setup.

The following sections provide an overview of the key catalogs available in Docker Hub.

MCP Catalog

The MCP Catalog is a centralized, trusted registry for discovering, sharing, and running Model Context Protocol (MCP)-compatible tools. Seamlessly integrated into Docker Hub, the catalog includes:

• Over 100 verified MCP servers packaged as Docker images
• Tools from partners such as New Relic, Stripe, and Grafana
• Versioned releases with publisher verification
• Simplified pull-and-run support through Docker Desktop and Docker CLI

Each server runs in an isolated container to ensure consistent behavior and minimize configuration headaches. For developers working with Claude Desktop or other MCP clients, the catalog provides an easy way to extend functionality with drop-in tools.

To learn more about MCP servers, see MCP Catalog and Toolkit.

AI Models Catalog

The AI Models Catalog provides curated, trusted models that work with Docker Model Runner. This catalog is designed to make AI development more accessible by offering pre-packaged, ready-to-use models that you can pull, run, and interact with using familiar Docker tools.

With the AI Models Catalog and Docker Model Runner, you can:

• Pull and serve models from Docker Hub or any OCI-compliant registry
• Interact with models via OpenAI-compatible APIs
• Run and test models locally using Docker Desktop or CLI
• Package and publish models using the docker model CLI

Whether you're building generative AI applications, integrating LLMs into your workflows, or experimenting with machine learning tools, the AI Models Catalog simplifies the model management experience.