AI agents call get_author_papers to retrieve information from Semanticscholar without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and returns academic paper data associated with an author. It performs a read-only retrieval operation without creating, modifying, deleting, or executing any code. The function falls clearly under the 'Read' category as it searches and fetches information from the Semantic Scholar database.
From the tool's definition Tool name 'get_author_papers' and description '获取指定作者的论文列表' (retrieves list of papers by a specified author) indicate a data retrieval operation with no side effects.
Documented attack patterns abuse exactly the kind of access get_author_papers gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Semanticscholar, and nothing reaches the server without passing your rules. This is the rule we recommend for get_author_papers:
{
"version": "1",
"default": "deny",
"tools": {
"get_author_papers": {}
}
}get_author_papers is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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获取指定作者的论文列表. It is categorised as a Read tool in the Semanticscholar MCP Server, which means it retrieves data without modifying state.
Register the Semanticscholar MCP server in PolicyLayer and add a rule for get_author_papers: 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 Semanticscholar. Nothing to install.
get_author_papers 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 get_author_papers 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 get_author_papers. 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.
get_author_papers is provided by the Semanticscholar MCP server (xbghc/semanticscholar-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Semanticscholar, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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9 Semanticscholar tools catalogued and risk-classified — across an index of 43,000+ MCP servers.