AI agents call author_details to retrieve information from Semantic Scholar 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 or queries author data from the Semantic Scholar API. It performs no side effects, creates no data, executes no code, and makes no financial transactions. The tool is purely a data retrieval operation, fitting the Read category. Confidence is slightly reduced due to empty description, but the sibling tools and server context provide sufficient context to classify with reasonable confidence.
From the tool's definition Tool name is 'author_details' with empty description. Sibling tools (author_batch_details, author_papers, author_search, paper_authors, etc.) are all retrieval operations.
Documented attack patterns abuse exactly the kind of access author_details gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Semantic Scholar MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for author_details:
{
"version": "1",
"default": "deny",
"tools": {
"author_details": {}
}
}author_details is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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author_details. It is categorised as a Read tool in the Semantic Scholar MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Semantic Scholar MCP Server MCP server in PolicyLayer and add a rule for author_details: 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 Semantic Scholar MCP Server. Nothing to install.
author_details 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 author_details 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 author_details. 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.
author_details is provided by the Semantic Scholar MCP Server MCP server (zongmin-yu/semantic-scholar-fastmcp-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 16 Semantic Scholar MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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16 Semantic Scholar MCP Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.