This record as markdown: /tools/coolify/start-service.md
What start_service does on Coolify
AI agents invoke start_service to trigger actions in Coolify. 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 start_service is rated High
This tool executes an external action (starting a service) that can have cascading effects on running systems, deployments, or infrastructure. While not permanently destructive or financial, misuse (e.g., starting unintended critical services, causing resource exhaustion, or triggering dependent operations) poses significant operational risk.
From the tool's definition Tool name 'start_service' and description 'Start a service' indicate execution of a service start operation, which triggers external system behavior.
Attacks that exploit this kind of access
The rule that runs start_service safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Coolify, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For start_service, this is the rule to start with:
start_service 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 Coolify, apply this rule, and every start_service call is checked against it from then on.
Questions about start_service
Start a service. It is categorised as a Execute tool in the Coolify MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Coolify MCP server in PolicyLayer and add a rule for start_service: 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 Coolify. Nothing to install.
start_service 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 start_service 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 start_service. 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.
start_service is provided by the Coolify MCP server (coolify-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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