Deploy a service from the catalog by creating VM and configuring it
AI agents invoke deploy-service to trigger actions in Ansible. 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.
This tool executes external operations that create and configure virtual machines. While it creates resources (which could be considered Write), the creation of infrastructure through VM provisioning is an external operation execution that warrants Execute classification.
From the tool's definition Tool description states 'Deploy a service from the catalog by creating VM and configuring it' — this involves executing infrastructure provisioning operations (VM creation and configuration) whose effects depend on runtime arguments.
Documented attack patterns abuse exactly the kind of access deploy-service gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Ansible, and nothing reaches the server without passing your rules. This is the rule we recommend for deploy-service:
{
"version": "1",
"default": "deny",
"tools": {
"deploy-service": {
"limits": [
{
"counter": "deploy-service_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}deploy-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.
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Deploy a service from the catalog by creating VM and configuring it. It is categorised as a Execute tool in the Ansible MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Ansible MCP server in PolicyLayer and add a rule for deploy-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 Ansible. Nothing to install.
deploy-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 deploy-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 deploy-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.
deploy-service is provided by the Ansible MCP server (washyu/ansible-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Ansible, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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90 Ansible tools catalogued and risk-classified — across an index of 43,000+ MCP servers.