Model Context Protocol (MCP) servers are a spec for exposing tools, models, or services to language models through a common interface. Think of them as smart adapters: they sit between a tool and the LLM, speaking a predictable protocol that lets the model interact with things like APIs, databases, and agents without needing to know implementation details.
But like most good ideas, the devil’s in the details.
The Promise—and the Problems of Running MCP Servers
Running an MCP sounds simple: spin up a Python or Node server that exposes your tool. Done, right? Not quite.
You run into problems fast:
- Runtime friction: If an MCP is written in Python, your environment needs Python (plus dependencies, plus maybe a virtualenv strategy, plus maybe GPU drivers). Same goes for Node. This multiplies fast when you’re managing many MCPs or deploying them across teams.
- Secrets management: MCPs often need credentials (API keys, tokens, etc.). You need a secure way to store and inject those secrets into your MCP runtime. That gets tricky when different teams, tools, or clouds are involved.
- N×N integration pain: Let’s say you’ve got three clients that want to consume MCPs, and five MCPs to serve up. Now you’re looking at 15 individual integrations. No thanks.
To make MCPs practical, you need to solve these three core problems: runtime complexity, secret injection, and client-to-server wiring.
If you’re wondering where I’m going with all this, take a look at those problems. We already have a technology that has been used by developers for over a decade that helps solve them: Docker containers.
In the rest of this blog I’ll walk through three different approaches, going from least complex to most complex, for integrating MCP servers into your developer experience.
Option 1 — Docker MCP Toolkit & Catalog
For the developer who already uses containers and wants a low-friction way to start with MCP.
If you’re already comfortable with Docker but just getting your feet wet with MCP, this is the sweet spot. In the raw MCP world, you’d clone Python/Node servers, manage runtimes, inject secrets yourself, and hand-wire connections to every client. That’s exactly the pain Docker’s MCP ecosystem set out to solve.
Docker’s MCP Catalog is a curated, containerized registry of MCP servers. Each entry is a prebuilt container with everything you need to run the MCP server.
The MCP Toolkit (available via Docker Desktop) is your control panel: search the catalog, launch servers with secure defaults, and connect them to clients.
How it helps: