rerank_papers

Rerank a set of papers by quality signals. Takes DOIs or paper IDs from search results,

Server Paper Search upascal/paper-search-mcp
Category Read
Risk class Low
Parameters 00 required

What rerank_papers does on Paper Search

AI agents call rerank_papers to retrieve information from Paper Search without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Why rerank_papers needs a policy

Reranking is a read/compute operation that takes existing paper identifiers and returns them in a new order based on quality signals. No data is created, modified, deleted, or any external system triggered. The blast radius of misuse is minimal — at worst an AI agent gets a suboptimal ordering of papers.

From the tool's definition 'Rerank a set of papers by quality signals. Takes DOIs or paper IDs from search results' — this operation reorders/scores existing data without modifying or deleting anything

Questions about rerank_papers

What does the rerank_papers tool do? +

Rerank a set of papers by quality signals. Takes DOIs or paper IDs from search results,. It is categorised as a Read tool in the Paper Search MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on rerank_papers? +

Register the Paper Search MCP server in PolicyLayer and add a rule for rerank_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 Paper Search. Nothing to install.

What risk level is rerank_papers? +

rerank_papers is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit rerank_papers? +

Yes. Add a rate_limit block to the rerank_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.

How do I block rerank_papers completely? +

Set action: deny in the PolicyLayer policy for rerank_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.

What MCP server provides rerank_papers? +

rerank_papers is provided by the Paper Search MCP server (upascal/paper-search-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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