2026-03-22DockerAI agentsno-codeopen sourceautomation

Docker just let anyone build AI agents — no code needed

Docker Agent turns simple YAML files into multi-agent AI teams. Works with any AI model, runs locally, and ships as a single Docker command.

Docker — the company that made software containers a household word for developers — just released Docker Agent, an open-source tool that lets anyone build, run, and orchestrate AI agents using nothing more than a simple configuration file.

No Python scripts. No frameworks to learn. Just write a short YAML file (a plain-text recipe), type docker agent run, and watch your AI agent come to life. It's already at 2,600 GitHub stars with 70 contributors and daily releases.

Docker Agent demo showing an AI agent running from the command line

One YAML file, one command, one AI agent

Here's how simple it is. This config file creates an AI assistant with web search:

agents:
  root:
    model: openai/gpt-5-mini
    description: A helpful AI assistant
    instruction: |
      You are a knowledgeable assistant.
      Be helpful, accurate, and concise.
    toolsets:
      - type: mcp
        ref: docker:duckduckgo

Then run it:

docker agent run agent.yaml

That's it. Your agent can now search the web and answer questions. No API wrappers, no boilerplate, no dependency hell.

Build a team of AI agents that talk to each other

The real power is multi-agent orchestration. You can define multiple specialized agents in a single YAML file — a researcher, a writer, a fact-checker — and they automatically delegate tasks to each other.

What Docker Agent gives you out of the box:

Any AI model — OpenAI, Anthropic Claude, Google Gemini, AWS Bedrock, or local models via Ollama
MCP tool support — connect agents to web search, databases, file systems, and hundreds of other tools using the Model Context Protocol (the universal plug system for AI)
Built-in RAG — agents can search through your documents and files to find answers (Retrieval-Augmented Generation makes AI reference your actual data instead of guessing)
Memory — agents remember context across conversations
Agent catalog — pull pre-built agents like Docker images: docker agent run agentcatalog/pirate

Why Docker makes this different

There are dozens of AI agent frameworks. What makes Docker Agent stand out is the same thing that made Docker containers win: it eliminates setup pain.

If you have Docker Desktop 4.63 or newer, Docker Agent is already installed. No extra downloads. The agents run inside Docker's secure container environment, so they can't accidentally delete your files or access things they shouldn't.

Docker also lets you package and share agents through OCI registries (the same system developers use to distribute container images). Build an agent, push it to a registry, and anyone can pull and run it with a single command.

Who should try this

Office workers and marketers: Set up an agent that searches the web and summarizes findings — no coding needed, just edit the YAML instructions.

Developers: Skip the framework learning curve. Define agents in config, version-control them with Git, and distribute them like any other Docker artifact.

Teams: Build multi-agent workflows where a research agent finds data, an analysis agent processes it, and a writing agent produces the report — all coordinated automatically.

Get started in 60 seconds

# If you have Docker Desktop 4.63+, it's already there:
docker agent run

# Or install via Homebrew:
brew install docker-agent

# Create a new agent interactively:
docker agent new

# Run a pre-built agent from the catalog:
docker agent run agentcatalog/pirate

You'll need an API key from your preferred AI provider (OpenAI, Anthropic, etc.) set as an environment variable. The project is Apache-2.0 licensed — fully free and open-source.

Docker Agent is releasing updates almost daily (v1.36.0 dropped March 20), adding features like WebSocket streaming, session management, and improved tool handling. The GitHub repository has full documentation and examples.

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