AI agents call paper_detail to retrieve information from Mcp Scholar 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 detailed information about academic papers from Google Scholar without any side effects. It is a pure read operation that returns existing paper metadata and information. The severity is low because misuse would only expose publicly available academic paper information with no destructive or harmful consequences.
From the tool's definition Tool name 'paper_detail' with description '获取论文详细信息' (get paper detailed information) retrieves metadata and information about academic papers.
Documented attack patterns abuse exactly the kind of access paper_detail gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Mcp Scholar, and nothing reaches the server without passing your rules. This is the rule we recommend for paper_detail:
{
"version": "1",
"default": "deny",
"tools": {
"paper_detail": {}
}
}paper_detail is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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获取论文详细信息. It is categorised as a Read tool in the Mcp Scholar MCP Server, which means it retrieves data without modifying state.
Register the Mcp Scholar MCP server in PolicyLayer and add a rule for paper_detail: 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 Scholar. Nothing to install.
paper_detail 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 paper_detail 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 paper_detail. 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.
paper_detail is provided by the Mcp Scholar MCP server (renyumeng1/mcp_scholar). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 7 Mcp Scholar tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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7 Mcp Scholar tools catalogued and risk-classified — across an index of 42,500+ MCP servers.