This record as markdown: /tools/docker/create-container.md
What create_container does on Docker
AI agents invoke create_container to trigger actions in Docker. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why create_container is rated High
Creating a Docker container instantiates a new runtime environment that can execute arbitrary workloads, expose ports, mount volumes, and consume host resources. While it doesn't delete data, it triggers external operations with significant blast radius — a misconfigured or malicious container can compromise the host system, exfiltrate data, or serve as a pivot point.
From the tool's definition Tool name: 'create_container', description: 'Create a new Docker container'
Attacks that exploit this kind of access
The rule that runs create_container safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Docker, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For create_container, this is the rule to start with:
create_container stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Docker, apply this rule, and every create_container call is checked against it from then on.
Questions about create_container
Create a new Docker container. It is categorised as a Execute tool in the Docker MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Docker MCP server in PolicyLayer and add a rule for create_container: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Docker. Nothing to install.
create_container is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the create_container rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for create_container. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
create_container is provided by the Docker MCP server (@ckreiling/mcp-server-docker). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
More on Docker, and thousands of servers like it.
Across the catalogue