Run a full AEO (Answer Engine Optimization) audit for a domain. Checks how the domain appears across AI answer engines for given queries. Returns citation rate, grade (A-F), competitor comparison, and per-query results.
AI agents invoke audit_domain to trigger actions in AEO Audit. 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.
| Parameter | Type | Required | Description |
|---|---|---|---|
domain | string | Yes | The domain to audit (e.g., 'example.com') |
queries | array | Yes | Search queries to test |
provider | string | — | AI engine (default: exa) |
competitors | array | — | Competitor domains |
Parameters from the server's own tool schema.
This tool triggers an external operation (domain audit/crawling) whose effects depend on the argument (which domain is audited). It performs active checks against specified domains, making queries to AI answer engines and analyzing results.
From the tool's definition 'Run a full AEO audit for a domain' and 'Checks how the domain appears across AI answer engines for given queries' indicate the tool executes an audit operation against a target domain, performing external queries and analysis with side effects dependent on…
Attacks that exploit this kind of access
Run a full AEO (Answer Engine Optimization) audit for a domain. Checks how the domain appears across AI answer engines for given queries. Returns citation rate, grade (A-F), competitor comparison, and per-query results. It is categorised as a Execute tool in the AEO Audit MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
audit_domain accepts 4 parameters: domain, queries, provider, competitors. Required: domain, queries. The full parameter table on this page comes from the server's own tool schema.
Register the AEO Audit MCP server in PolicyLayer and add a rule for audit_domain: 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 AEO Audit. Nothing to install.
audit_domain 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 audit_domain 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 audit_domain. 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.
audit_domain is provided by the AEO Audit MCP server (https://aeo-mcp-server.amdal-dev.workers.dev/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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