Extract claims, methods, limitations, datasets, metrics, and section-aware summaries from a parsed document.
AI agents call extract_granular_paper_details to retrieve information from ScholarMCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool reads and analyzes structured data from academic papers that have already been ingested. It performs information extraction and summarization—classic Read operations. There is no modification of source data, no irreversible actions, no code execution, and no financial implications.
From the tool's definition Tool description specifies extraction of information from parsed documents: 'Extract claims, methods, limitations, datasets, metrics, and section-aware summaries from a parsed document.' This is a retrieval and analysis operation with no data modification,…
Documented attack patterns abuse exactly the kind of access extract_granular_paper_details gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and ScholarMCP, and nothing reaches the server without passing your rules. This is the rule we recommend for extract_granular_paper_details:
{
"version": "1",
"default": "deny",
"tools": {
"extract_granular_paper_details": {}
}
}extract_granular_paper_details is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Extract claims, methods, limitations, datasets, metrics, and section-aware summaries from a parsed document. It is categorised as a Read tool in the ScholarMCP MCP Server, which means it retrieves data without modifying state.
Register the Scholar MCP server in PolicyLayer and add a rule for extract_granular_paper_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 ScholarMCP. Nothing to install.
extract_granular_paper_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 extract_granular_paper_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 extract_granular_paper_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.
extract_granular_paper_details is provided by the Scholar MCP server (lstudlo/scholarmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from ScholarMCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
10 ScholarMCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.