Get a current, verified recommendation for a cloud service based on your constraints. Returns pricing, risks, provision commands, and alternatives. Data is Chrome-verified from actual service websites (not stale training data).
Part of the Auxiliar server.
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AI agents call recommend_service to retrieve information from Auxiliar without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though recommend_service only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
{
"version": "1",
"default": "deny",
"tools": {
"recommend_service": {}
}
}See the full Auxiliar policy for all 13 tools.
These attack patterns abuse exactly the kind of access recommend_service gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Get a current, verified recommendation for a cloud service based on your constraints. Returns pricing, risks, provision commands, and alternatives. Data is Chrome-verified from actual service websites (not stale training data).. It is categorised as a Read tool in the Auxiliar MCP Server, which means it retrieves data without modifying state.
Register the Auxiliar MCP server in PolicyLayer and add a rule for recommend_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 Auxiliar. Nothing to install.
recommend_service is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the recommend_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 recommend_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.
recommend_service is provided by the Auxiliar MCP server (auxiliar-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 13 Auxiliar tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
4,600+ MCP servers and 31,000+ tools scanned and risk-classified.