Search academic papers from Semantic Scholar. Args: query: Search query string (e.g., 'machine learning'). year: Optional year filter (e.g., '2019', '2016-2020', '2010-', '-2015'). max_results: Maximum number of papers to return (default: 10). Returns: List of paper metadata in dictionary format.
AI agents call search_semantic to retrieve information from Paper Search MCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
search_semantic retrieves and queries paper metadata from Semantic Scholar with optional filtering by year and result limit. It is a read-only operation with no side effects, matching the Read category definition. The severity is low because searching public academic papers poses minimal risk even if misused by an AI agent.
From the tool's definition Tool description states it 'Search[es] academic papers from Semantic Scholar' and 'Returns: List of paper metadata in dictionary format.' No modification, deletion, execution, or financial operations are performed.
Documented attack patterns abuse exactly the kind of access search_semantic gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Paper Search MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for search_semantic:
{
"version": "1",
"default": "deny",
"tools": {
"search_semantic": {}
}
}search_semantic is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Search academic papers from Semantic Scholar. Args: query: Search query string (e.g., 'machine learning'). year: Optional year filter (e.g., '2019', '2016-2020', '2010-', '-2015'). max_results: Maximum number of papers to return (default: 10). Returns: List of paper metadata in dictionary format. It is categorised as a Read tool in the Paper Search MCP MCP Server, which means it retrieves data without modifying state.
Register the Paper Search MCP server in PolicyLayer and add a rule for search_semantic: 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 Paper Search MCP. Nothing to install.
search_semantic 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 search_semantic 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 search_semantic. 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.
search_semantic is provided by the Paper Search MCP server (openags/paper-search-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 63 Paper Search MCP tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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63 Paper Search MCP tools catalogued and risk-classified — across an index of 42,500+ MCP servers.