`search_papers`

Pack: semantic-scholar · Endpoint: https://gateway.pipeworx.io/semantic-scholar/mcp

Search academic papers across all fields of science. Returns title, abstract, TL;DR summary, authors, citation count, year, journal, and open access PDF links. Example: search_papers(“transformer attention mechanism”, year=“2023”)

Parameters

Name	Type	Required	Description
`query`	string	yes	Search keywords (e.g., “CRISPR gene editing”, “large language models”)
`year`	string	no	Filter by year or range (e.g., “2023”, “2020-2024”)
`limit`	number	no	Max papers to return (1-100, default 10)

Example call

Arguments

{
  "query": "transformer attention mechanism",
  "year": "2023",
  "limit": 10
}

curl

curl -X POST https://gateway.pipeworx.io/semantic-scholar/mcp \
  -H 'Content-Type: application/json' \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"search_papers","arguments":{"query":"transformer attention mechanism","year":"2023","limit":10}}}'

TypeScript (@pipeworx/sdk)

import { Pipeworx } from '@pipeworx/sdk';
const pipeworx = new Pipeworx();

const result = await pipeworx.call('search_papers', {
  "query": "transformer attention mechanism",
  "year": "2023",
  "limit": 10
});

More examples

{
  "query": "CRISPR gene editing",
  "year": "2020-2024",
  "limit": 20
}

Response shape

Always returns: query, total, returned, papers

Field	Type	Description
`query`	string	The search query used
`total`	number	Total number of matching papers
`returned`	number	Number of papers returned in this response
`papers`	array	List of papers matching the search

Full JSON Schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "The search query used"
    },
    "total": {
      "type": "number",
      "description": "Total number of matching papers"
    },
    "returned": {
      "type": "number",
      "description": "Number of papers returned in this response"
    },
    "papers": {
      "type": "array",
      "description": "List of papers matching the search",
      "items": {
        "type": "object",
        "properties": {
          "paper_id": {
            "type": [
              "string",
              "null"
            ],
            "description": "Semantic Scholar paper ID"
          },
          "title": {
            "type": [
              "string",
              "null"
            ],
            "description": "Paper title"
          },
          "abstract": {
            "type": [
              "string",
              "null"
            ],
            "description": "Paper abstract"
          },
          "tldr": {
            "type": [
              "string",
              "null"
            ],
            "description": "TL;DR summary of the paper"
          },
          "year": {
            "type": [
              "number",
              "null"
            ],
            "description": "Publication year"
          },
          "publication_date": {
            "type": [
              "string",
              "null"
            ],
            "description": "Full publication date"
          },
          "citation_count": {
            "type": [
              "number",
              "null"
            ],
            "description": "Number of citations"
          },
          "influential_citations": {
            "type": [
              "number",
              "null"
            ],
            "description": "Number of influential citations"
          },
          "reference_count": {
            "type": [
              "number",
              "null"
            ],
            "description": "Number of references in the paper"
          },
          "is_open_access": {
            "type": [
              "boolean",
              "null"
            ],
            "description": "Whether the paper is open access"
          },
          "open_access_pdf": {
            "type": [
              "string",
              "null"
            ],
            "description": "URL to open access PDF if available"
          },
          "fields_of_study": {
            "type": "array",
            "description": "Fields of study tags",
            "items": {
              "type": "string"
            }
          },
          "publication_types": {
            "type": "array",
            "description": "Publication type tags",
            "items": {
              "type": "string"
            }
          },
          "journal": {
            "type": [
              "string",
              "null"
            ],
            "description": "Journal name"
          },
          "venue": {
            "type": [
              "string",
              "null"
            ],
            "description": "Publication venue"
          },
          "url": {
            "type": [
              "string",
              "null"
            ],
            "description": "URL to the paper"
          },
          "doi": {
            "type": [
              "string",
              "null"
            ],
            "description": "Digital Object Identifier"
          },
          "authors": {
            "type": "array",
            "description": "Paper authors",
            "items": {
              "type": "object",
              "properties": {
                "id": {
                  "type": [
                    "string",
                    "null"
                  ],
                  "description": "Author ID"
                },
                "name": {
                  "type": [
                    "string",
                    "null"
                  ],
                  "description": "Author name"
                }
              }
            }
          }
        }
      }
    }
  },
  "required": [
    "query",
    "total",
    "returned",
    "papers"
  ]
}

Connect

Add this to your MCP client config, or use one-click install buttons:

{
  "mcpServers": {
    "semantic-scholar": {
      "url": "https://gateway.pipeworx.io/semantic-scholar/mcp"
    }
  }
}

See Getting Started for client-specific install steps.

search_papers