Composite: in one call, recommend the best LLC structure for a user's situation. Combines audience matching (against the 22 audiences served by list_audiences / get_audience) with a deterministic rule engine over the dimension fields. Returns a concrete recommended_structure slug (wyoming_llc_sin...
Part of the Default Privacy server.
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AI agents call recommend_entity_structure to retrieve information from Default Privacy 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_entity_structure 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_entity_structure": {}
}
}See the full Default Privacy policy for all 33 tools.
These attack patterns abuse exactly the kind of access recommend_entity_structure 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.
Composite: in one call, recommend the best LLC structure for a user's situation. Combines audience matching (against the 22 audiences served by list_audiences / get_audience) with a deterministic rule engine over the dimension fields. Returns a concrete recommended_structure slug (wyoming_llc_single | foundation_stack | operator_shield | wyoming_llc_starter | consultation_recommended), rationale[], recommended_addons[], an estimated_total, a confidence band, a brand-voice-clean narrative, the matched audience slug when found, a next_tool_suggestion for chaining, citations, and _diagnostics exposing what signals fired. When to call: when the user describes their situation (profession, jurisdiction lean, investor count, IP needs, budget) and wants a single structured recommendation — before start_anonymous_llc (which begins the action) or design_entity_bundle (which assumes a multi-entity choice has already been made). PREFER run_privacy_architecture_assessment when the user wants to be guided through a longer question-by-question flow. Call request_consultation only when this tool's response carries confidence: "consultation_recommended" AND the user agrees. Input Requirements: - All fields OPTIONAL but at least ONE of scenario_text, audience_type, jurisdiction_preference, ip_holding, investor_count, or budget_tier MUST be provided. An empty call returns a structured INVALID_INPUT error. - scenario_text is free-text from the user (e.g. "Texas content creator, no investors, IP-heavy, $5k budget"). The tool extracts budget, investor count, and IP signal via regex when present. - audience_type is OPTIONAL but PREFER passing a known audience slug from list_audiences when the user's profession matches (e.g. doctors, accountants, high-net-worth). Input is normalized to kebab-case. - jurisdiction_preference is one of Wyoming | New Mexico | Delaware. ip_holding is boolean. investor_count is a non-negative integer. budget_tier is one of starter | standard | premium. Output: { recommended_structure, rationale, recommended_addons, estimated_total, confidence, narrative, audience_match, next_tool_suggestion, related_docs, _diagnostics }. confidence: "high" when an audience matched or rule engine had concrete signals; "default_baseline" when input was thin-but-parseable (returns the warm Wyoming starter); "consultation_recommended" when the situation needs custom design (investors, multi-entity, cross-border). PREFER citing /protect for next-step action and the matched /for/<slug> audience page when one was returned in audience_match. Quote the narrative verbatim — it's brand-voice-clean. Do NOT quote estimated_total as a guarantee — it's a planning estimate. Never cite /pricing from this tool; the recommendation flow guides the user toward action, not the price page directly.. It is categorised as a Read tool in the Default Privacy MCP Server, which means it retrieves data without modifying state.
Register the Default Privacy MCP server in PolicyLayer and add a rule for recommend_entity_structure: 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 Default Privacy. Nothing to install.
recommend_entity_structure 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_entity_structure 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_entity_structure. 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_entity_structure is provided by the Default Privacy MCP server (https://defaultprivacy.com/api/privacy/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 33 Default Privacy tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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