Docker Agent

What Is Docker Agent?

Docker Agent is an open-source tool from Docker that lets you build, run, and share AI agents using simple configuration files instead of writing application code.

You describe what your agent does — its model, personality, tools, and teammates — in a YAML file. Docker Agent handles the LLM orchestration loop, tool execution, multi-agent delegation, and streaming output. You focus on what the agent should do, not how to wire it up.

# agent.yaml — this is all you need
agents:
  root:
    model: anthropic/claude-sonnet-4-5
    description: A coding assistant
    instruction: |
      You are an expert developer. Help users write clean,
      efficient code. Explain your reasoning step by step.
    toolsets:
      - type: filesystem
      - type: shell
      - type: think

$ docker agent run agent.yaml

That’s it. Your agent can now read and write files, run shell commands, and reason through problems — all through an interactive terminal UI.

See It in Action

Why Docker Agent?

Most AI agent frameworks ask you to write Python or TypeScript to glue together models, tools, and workflows. Docker Agent takes a different approach: declare everything in config, run it with a single command.

How It Works

Docker Agent follows a simple loop:

1. You define an agent in YAML — its model, instructions, tools, and sub-agents
2. You run it with docker agent run via TUI, CLI, or API
3. The agent processes your request — calling tools, delegating to sub-agents, reasoning step by step
4. Results stream back in real time

Zero Config

The fastest way to try it — no config file needed:

# Run the built-in default agent
$ docker agent run

From the Registry

Run pre-built agents from the agent catalog — just like pulling a Docker image:

# A pirate-themed assistant
$ docker agent run agentcatalog/pirate

# A coding agent
$ docker agent run agentcatalog/coder

Multi-Agent Teams

Build a team where a coordinator delegates tasks to specialists:

agents:
  root:
    model: openai/gpt-5
    description: Team coordinator
    instruction: Route tasks to the best specialist.
    sub_agents: [coder, reviewer]

  coder:
    model: anthropic/claude-sonnet-4-5
    description: Writes and modifies code
    instruction: Write clean, tested code.
    toolsets:
      - type: filesystem
      - type: shell

  reviewer:
    model: anthropic/claude-sonnet-4-5
    description: Reviews code for quality
    instruction: Review code for bugs, style, and best practices.
    toolsets:
      - type: filesystem

Non-Interactive Mode

Use --exec for scripting and automation:

# One-shot task
$ docker agent run --exec agent.yaml "Create a Dockerfile for a Node.js app"

# Pipe input
$ cat error.log | docker agent run --exec agent.yaml "What's wrong in this log?"

# Serve as an API
$ docker agent serve api agent.yaml --listen :8080

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