This record as markdown: /tools/io-github-portel-dev-ncp/stop-container.md
What stop_container does on Ncp
AI agents invoke stop_container to trigger actions in Ncp. 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 stop_container is rated High
Stopping a container is an Execute action because it runs/triggers an external operation (Docker daemon command) whose effects depend on which container is targeted. While not permanently destructive (containers can be restarted), it immediately halts running processes and services, making it high severity.
From the tool's definition Tool description states 'Stop a running Docker container' — this directly triggers external operations with immediate effects on container state and running processes.
Attacks that exploit this kind of access
The rule that runs stop_container safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Ncp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For stop_container, this is the rule to start with:
stop_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 Ncp, apply this rule, and every stop_container call is checked against it from then on.
Questions about stop_container
Stop a running Docker container. It is categorised as a Execute tool in the Ncp MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Ncp MCP server in PolicyLayer and add a rule for stop_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 Ncp. Nothing to install.
stop_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 stop_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 stop_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.
stop_container is provided by the Ncp MCP server (@portel/ncp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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