๐ฑ๐ Analyze keyword performance by device within shopping categories. Use find_category first to get category codes. Perfect for understanding mobile vs desktop shopping behavior for specific products. (์ผํ ํค์๋ ๊ธฐ๊ธฐ๋ณ ํธ๋ ๋ - ๋จผ์ find_category ๋๊ตฌ๋ก ์นดํ ๊ณ ๋ฆฌ ์ฝ๋๋ฅผ ์ฐพ์ผ์ธ์)
AI agents call datalab_shopping_keyword_by_device to retrieve information from Naver Search MCP Server without modifying anything โ typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and returns analytics data about shopping keyword trends segmented by device type. It retrieves pre-computed or aggregated metrics from Naver's datalab without creating, modifying, executing code, deleting data, or moving money. The use case is passive analysis of shopping behavior trends. No side effects or state changes occur.
From the tool's definition Tool description states it 'Analyze[s] keyword performance' and is for 'understanding mobile vs desktop shopping behavior' โ purely analytical/retrieval operations with no modification or execution of external systems.
Documented attack patterns abuse exactly the kind of access datalab_shopping_keyword_by_device gives an agent:
PolicyLayer is an MCP gateway โ it sits between your AI agents and Naver Search MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for datalab_shopping_keyword_by_device:
{
"version": "1",
"default": "deny",
"tools": {
"datalab_shopping_keyword_by_device": {}
}
}datalab_shopping_keyword_by_device is read-only, so it stays allowed โ but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
๐ฑ๐ Analyze keyword performance by device within shopping categories. Use find_category first to get category codes. Perfect for understanding mobile vs desktop shopping behavior for specific products. (์ผํ ํค์๋ ๊ธฐ๊ธฐ๋ณ ํธ๋ ๋ - ๋จผ์ find_category ๋๊ตฌ๋ก ์นดํ ๊ณ ๋ฆฌ ์ฝ๋๋ฅผ ์ฐพ์ผ์ธ์). It is categorised as a Read tool in the Naver Search MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Naver Search MCP Server MCP server in PolicyLayer and add a rule for datalab_shopping_keyword_by_device: 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 Naver Search MCP Server. Nothing to install.
datalab_shopping_keyword_by_device 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 datalab_shopping_keyword_by_device 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 datalab_shopping_keyword_by_device. 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.
datalab_shopping_keyword_by_device is provided by the Naver Search MCP Server MCP server (isnow890/naver-search-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Naver Search MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
21 Naver Search MCP Server tools catalogued and risk-classified โ across an index of 43,000+ MCP servers.