Academic Paper Search MCP Server

AGPL 3.0

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fetch_paper_details

Retrieve comprehensive metadata for academic papers by specifying a paper identifier (DOI or ID) and source database (Semantic Scholar or Crossref). Supports structured data integration for AI-driven research tools.

Instructions

Get detailed information about a specific paper.

Args:
    paper_id: Paper identifier (DOI for Crossref, paper ID for Semantic Scholar)
    source: Source database ("semantic_scholar" or "crossref")

Input Schema

Name	Required	Description	Default
`paper_id`	Yes
`source`	No		semantic_scholar

Input Schema (JSON Schema)

{
  "properties": {
    "paper_id": {
      "title": "Paper Id",
      "type": "string"
    },
    "source": {
      "default": "semantic_scholar",
      "title": "Source",
      "type": "string"
    }
  },
  "required": [
    "paper_id"
  ],
  "title": "fetch_paper_detailsArguments",
  "type": "object"
}

Install Server

HTTP connection URL

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