get_paper_recommendations_single
AI agents call get_paper_recommendations_single 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 paper recommendations based on a single paper input, with no indication of modifying, deleting, executing code, or financial operations. The empty description and naming pattern are consistent with other Read-category tools on this server that query the Semantic Scholar API.
From the tool's definition Tool name 'get_paper_recommendations_single' indicates retrieval of recommendation data. Sibling tools like 'author_details', 'paper_citations', 'author_papers' are all Read operations querying academic data without modification.
Documented attack patterns abuse exactly the kind of access get_paper_recommendations_single 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 get_paper_recommendations_single:
{
"version": "1",
"default": "deny",
"tools": {
"get_paper_recommendations_single": {}
}
}get_paper_recommendations_single is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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get_paper_recommendations_single. 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 get_paper_recommendations_single: 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.
get_paper_recommendations_single 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_paper_recommendations_single 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_paper_recommendations_single. 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_paper_recommendations_single 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.