Get reviews of an app from Google Play Store
AI agents call gplay_reviews to retrieve information from Mcp Store Scraper without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves publicly available app reviews from Google Play Store. It queries and returns data without side effects—no data is created, modified, or deleted. This is a classic read operation with minimal risk exposure.
From the tool's definition Tool name 'gplay_reviews' and description 'Get reviews of an app from Google Play Store' indicate retrieval of existing data with no modification, creation, or deletion.
Attacks that exploit this kind of access
Get reviews of an app from Google Play Store. It is categorised as a Read tool in the Mcp Store Scraper MCP Server, which means it retrieves data without modifying state.
Register the Mcp Store Scraper MCP server in PolicyLayer and add a rule for gplay_reviews: 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 Store Scraper. Nothing to install.
gplay_reviews 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 gplay_reviews 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 gplay_reviews. 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.
gplay_reviews is provided by the Mcp Store Scraper MCP server (lucasmonteiro1/mcp-store-scraper). 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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