[API] Trigger a new deployment for a service ⚡️ Best for: ✓ Deploying code changes ✓ Applying configuration updates ✓ Rolling back to previous states ⚠️ Not for: × Restarting services (use service_restart) × Updating service config (use service_update) × Database changes → Prerequisites: service_...
Part of the Railway MCP Server server.
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AI agents invoke deployment_trigger to trigger processes or run actions in Railway MCP Server. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.
deployment_trigger can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.
Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.
{
"version": "1",
"default": "deny",
"tools": {
"deployment_trigger": {
"limits": [
{
"counter": "deployment_trigger_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}See the full Railway MCP Server policy for all 38 tools.
These attack patterns abuse exactly the kind of access deployment_trigger gives an agent. Each links to the full case and the policy that stops it:
Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
[API] Trigger a new deployment for a service ⚡️ Best for: ✓ Deploying code changes ✓ Applying configuration updates ✓ Rolling back to previous states ⚠️ Not for: × Restarting services (use service_restart) × Updating service config (use service_update) × Database changes → Prerequisites: service_list → Alternatives: service_restart → Next steps: deployment_logs, deployment_status → Related: variable_set, service_update. It is categorised as a Execute tool in the Railway MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Railway MCP Server MCP server in PolicyLayer and add a rule for deployment_trigger: 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 Railway MCP Server. Nothing to install.
deployment_trigger 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 deployment_trigger 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 deployment_trigger. 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.
deployment_trigger is provided by the Railway MCP Server MCP server (jason-tan-swe/railway-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 38 Railway MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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