Docker has announced two new AI-focused tools—the Docker MCP Catalog and the Docker MCP Toolkit—to bring container-grade security and developer-friendly workflows to agentic applications, helping build a developer-centric ecosystem for Model Context Protocol (MCP) tools.
The Docker MCP Catalog is a centralized platform for developers to discover MCP tools. Docker’s COO Mark Cavage and head of enfinnering Tushar Jain compare the current AI landscape to the early days of cloud computing and containers, highlighting the need for standardized tooling and secure, scalable development workflows.
Back in the early days of the cloud, Docker brought structure to chaos by making immutability and isolation the standard, building in authentication, and launching Docker Hub as a central discovery layer. It didn’t just streamline deployment – it redefined how software gets built, shared, and trusted.
Docker has partnered with companies across cloud, developer tooling, and AI, to build a catalog of over 100 MCP servers, all hosted on Docker Hub. The catalog includes tools from Stripe, Elastic, Neo4j, and more. Each tool is curated, verified, and versioned to ensure reliability and consistency.
The Docker MCP Toolkit allows developers to run, authenticate, and manage MCP tools from the Docker MCP Catalog directly on their development machines using the new docker mcp CLI command.
With one-click launch from Docker Desktop, you can spin up MCP servers in seconds and connect them to clients like Docker AI Agent, Claude, Cursor, VS Code, Windsurf, continue.dev, and Goose – no complex setup required
The toolkit also includes built-in credentials and OAuth support along with a Gateway MCP Server that dynamically exposes enabled tools to compatible clients.
Introduced by Anthropic, the Model Context Protocol is an open standard for integrating external resources and tools into LLM-centered apps. Built on a client-server architecture, MCP enables an app to use an MCP client to connect to MCP servers that provide access to datasources or external tools. Anthropic’s official documentation shows how a developer can implement an MCP server using Python to wrap calls to a public weather service. Any MCP-compliant app, such as Claude for Desktop, can then access this server without modifications.
Since its introduction, MCP has seen wide adoption—most recently from GitHub and Cloudflare—and has inspired the creation of several static and dynamic MCP server catalogs.
