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start_inquiry

Generate a WhatsApp inquiry link for a Fursat home. Returns a wa.me URL that opens WhatsApp with a prefilled message identifying the listing and (optionally) the guest's dates, party size, and notes. Use this when a traveler wants to actually book or inquire about a specific home after seeing it ...

Part of the Fursat server.

start_inquiry can trigger actions in Fursat, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents invoke start_inquiry to trigger processes or run actions in Fursat. 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.

start_inquiry 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.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "start_inquiry": {
      "limits": [
        {
          "counter": "start_inquiry_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Fursat policy for all 3 tools.

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These attack patterns abuse exactly the kind of access start_inquiry gives an agent. Each links to the full case and the policy that stops it:

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so start_inquiry only ever does what you allow.

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Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the start_inquiry tool do? +

Generate a WhatsApp inquiry link for a Fursat home. Returns a wa.me URL that opens WhatsApp with a prefilled message identifying the listing and (optionally) the guest's dates, party size, and notes. Use this when a traveler wants to actually book or inquire about a specific home after seeing it in search results. Bookings on Fursat happen on WhatsApp — there is no online checkout.. It is categorised as a Execute tool in the Fursat MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on start_inquiry? +

Register the Fursat MCP server in PolicyLayer and add a rule for start_inquiry: 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 Fursat. Nothing to install.

What risk level is start_inquiry? +

start_inquiry is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit start_inquiry? +

Yes. Add a rate_limit block to the start_inquiry 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.

How do I block start_inquiry completely? +

Set action: deny in the PolicyLayer policy for start_inquiry. 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.

What MCP server provides start_inquiry? +

start_inquiry is provided by the Fursat MCP server (https://www.fursat.fun/api/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Fursat tool call.

Deterministic rules across all 3 Fursat tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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