Get personalized performer recommendations based on performers, events, or location. This tool first searches for performers and/or events based on the queries, then uses the IDs to find similar performers. Use location parameters (geoip, lat/lon, postal_code) for nearby performers.
AI agents call find_performer_recommendations to retrieve information from SeatGeek MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and queries data from the SeatGeek API to provide performer recommendations. It takes search parameters (performers, events, location) and returns matching results. There are no side effects, no data modification, no code execution, and no financial transactions involved.
From the tool's definition Tool description states it 'searches for performers' and 'find[s] similar performers' - purely query and retrieval operations with no modification, deletion, execution, or financial impact. Returns personalized recommendations based on input parameters.
Attacks that exploit this kind of access
Get personalized performer recommendations based on performers, events, or location. This tool first searches for performers and/or events based on the queries, then uses the IDs to find similar performers. Use location parameters (geoip, lat/lon, postal_code) for nearby performers. It is categorised as a Read tool in the SeatGeek MCP Server MCP Server, which means it retrieves data without modifying state.
Register the SeatGeek MCP Server MCP server in PolicyLayer and add a rule for find_performer_recommendations: 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 SeatGeek MCP Server. Nothing to install.
find_performer_recommendations 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 find_performer_recommendations 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 find_performer_recommendations. 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.
find_performer_recommendations is provided by the SeatGeek MCP Server MCP server (petershin23/seatgeek-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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