semanticscholar.papers.get
Fetch full details for one academic paper by Semantic Scholar paper ID, DOI (e.g. "10.1038/nature14539"), or ArXiv ID (e.g. "ARXIV:1706.03762"). Returns title, full abstract, an AI-generated one-sentence TLDR summary, all authors, venue, fields of study, citation and reference counts, and open-ac...
This record as markdown: /tools/io-github-whiteknightonhorse-apibase/semanticscholar.papers.get.md
What semanticscholar.papers.get does on Apibase
AI agents call semanticscholar.papers.get to retrieve information from Apibase without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
paper_id | string | Yes | Semantic Scholar paper ID (40-char hash), DOI (e.g. "10.1038/nature14539"), or ArXiv ID (e.g. "ARXIV:1706.03762") to fetch full details for |
Parameters from the server's own tool schema.
Why semanticscholar.papers.get is rated Low
Retrieves publicly available academic paper metadata with no side effects or data modification capability.
From the tool's definition Fetch full details for one academic paper, Returns title, abstract, TLDR summary, authors, venue, citation counts.
Attacks that exploit this kind of access
The rule that runs semanticscholar.papers.get safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Apibase, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For semanticscholar.papers.get, this is the rule to start with:
semanticscholar.papers.get is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Apibase, apply this rule, and every semanticscholar.papers.get call is checked against it from then on.
Questions about semanticscholar.papers.get
Fetch full details for one academic paper by Semantic Scholar paper ID, DOI (e.g. "10.1038/nature14539"), or ArXiv ID (e.g. "ARXIV:1706.03762"). Returns title, full abstract, an AI-generated one-sentence TLDR summary, all authors, venue, fields of study, citation and reference counts, and open-access PDF link when available. Call semanticscholar.papers_search first to discover a paper_id from a text query. Data: api.semanticscholar.org, no auth required. It is categorised as a Read tool in the Apibase MCP Server, which means it retrieves data without modifying state.
semanticscholar.papers.get accepts 1 parameter: paper_id. Required: paper_id. The full parameter table on this page comes from the server's own tool schema.
Register the Apibase MCP server in PolicyLayer and add a rule for semanticscholar.papers.get: 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 Apibase. Nothing to install.
semanticscholar.papers.get 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 semanticscholar.papers.get 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 semanticscholar.papers.get. 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.
semanticscholar.papers.get is provided by the Apibase MCP server (apibase-mcp-client). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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