Compare AI visibility across multiple entities side-by-side. Probes each entity (your brand + N competitors) with ai_visibility_check, ranks by score, surfaces which is most/least recognized. Useful for competitive AI-marketing audits: "does Claude know about us as well as our competitors?". Retu...
AI agents call scan_competitor_ai_presence to retrieve information from Mcp Fbi Artcrimes without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
models | array | — | Which models to probe. Supported: "workers-ai" (free default), "anthropic" (requires _apiKey). Omit for just workers-ai. |
_apiKey | string | — | Optional Anthropic API key — only if "anthropic" is in models. Passed to api.anthropic.com per probe. |
context | string | — | Optional shared context applied to every probe (e.g. "B2B SaaS", "Boston restaurant"). Disambiguates common names. |
entities | array | Yes | Array of 2-8 entities to compare (brand/business/product names). First entry treated as the "subject" for narrative; rest are competitors. |
Parameters from the server's own tool schema.
This tool retrieves and compares information about AI visibility/recognition across entities. It reads data from the ai_visibility_check probe and aggregates it into a ranked report. There are no side effects: no data is created, modified, deleted, or irreversibly altered. It does not execute code or trigger financial transactions. The capability is purely informational/analytical.
From the tool's definition The tool 'Compare AI visibility across multiple entities side-by-side' and 'Returns ranked list with score, confidence, signal density per entity' describes querying and ranking data.
Attacks that exploit this kind of access
Compare AI visibility across multiple entities side-by-side. Probes each entity (your brand + N competitors) with ai_visibility_check, ranks by score, surfaces which is most/least recognized. Useful for competitive AI-marketing audits: "does Claude know about us as well as our competitors?". Returns ranked list with score, confidence, signal density per entity. It is categorised as a Read tool in the Mcp Fbi Artcrimes MCP Server, which means it retrieves data without modifying state.
scan_competitor_ai_presence accepts 4 parameters: models, _apiKey, context, entities. Required: entities. The full parameter table on this page comes from the server's own tool schema.
Register the Mcp Fbi Artcrimes MCP server in PolicyLayer and add a rule for scan_competitor_ai_presence: 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 Mcp Fbi Artcrimes. Nothing to install.
scan_competitor_ai_presence 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 scan_competitor_ai_presence 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 scan_competitor_ai_presence. 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.
scan_competitor_ai_presence is provided by the Mcp Fbi Artcrimes MCP server (pipeworx-io/mcp-fbi-artcrimes). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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