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Semantic Scholar

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from FujishigeTemma

Access Semantic Scholar's academic paper database through their API.

🔥🔥🔥✓ VerifiedAccount requiredNeeds API keys
#automation#database#documents#git#memory

Semantic Scholar MCP Server

Note: A lightweight CLI alternative is available at semantic-scholar-cli. It is designed for LLM tool-use workflows with strict typed inputs, stable JSON envelopes, and small default payloads — usable without an MCP server.

A Model Context Protocol (MCP) server that provides access to Semantic Scholar's academic paper database through their API.

Features

  • Paper Search: Search for academic papers with filters for year, fields of study, and open access
  • Paper Details: Get comprehensive information about specific papers including abstracts, authors, and citation counts
  • Author Information: Retrieve detailed author data including affiliations, h-index, and citation metrics
  • Citation Export: Generate citations in multiple formats (BibTeX, APA, MLA, Chicago)

Available Tools

  1. search_paper - Search for papers

    • Required: query (search terms)
    • Optional: fields, limit, offset, year, fieldsOfStudy, openAccessPdf

  2. get_paper - Get detailed paper information

    • Required: paper_id (supports multiple ID types: DOI, ArXiv ID, S2 Paper ID, etc.)
    • Optional: fields (customize returned data, see: Field Customization)

  3. get_authors - Get author information for a paper

    • Required: paper_id
    • Optional: fields, limit, offset

  4. get_citation - Generate formatted citations

    • Required: paper_id
    • Optional: format (bibtex, apa, mla, chicago)

CLI Examples

Search for papers:

semantic-scholar-mcp tools search_paper "machine learning" --limit 5 --year "2020-2023"

Get paper details:

semantic-scholar-mcp tools get_paper "10.1038/nature12373"

Get authors for a paper:

semantic-scholar-mcp tools get_authors "649def34f8be52c8b66281af98ae884c09aef38b"

Generate BibTeX citation:

semantic-scholar-mcp tools get_citation "649def34f8be52c8b66281af98ae884c09aef38b" --format bibtex

Field Customization

All tools support a fields parameter to customize the returned data. This allows you to request only the information you need, reducing response size and improving performance.

Paper Fields (for search_paper and get_paper)

Basic fields:

  • paperId - Unique paper identifier
  • title - Paper title
  • abstract - Paper abstract
  • year - Publication year
  • publicationDate - Full publication date

Author information:

  • authors - List of authors (returns authorId and name by default)
  • authors.authorId - Author's unique identifier
  • authors.name - Author's name
  • authors.affiliations - Author's institutional affiliations
  • authors.citationCount - Author's total citation count
  • authors.hIndex - Author's h-index

Citation and reference data:

  • citationCount - Number of times this paper has been cited
  • referenceCount - Number of references in this paper
  • citations - List of papers that cite this paper
  • references - List of papers referenced by this paper

Publication details:

  • journal - Journal information (name, volume, pages, etc.)
  • venue - Publication venue
  • publicationTypes - Types of publication (e.g., JournalArticle, Conference)
  • fieldsOfStudy - Academic fields (e.g., Computer Science, Medicine)
  • s2FieldsOfStudy - Semantic Scholar's field classifications

Additional metadata:

  • doi - Digital Object Identifier
  • arxivId - ArXiv identifier
  • url - Paper URL
  • openAccessPdf - Open access PDF information
  • embedding - Paper embedding vectors (for similarity analysis)

Author Fields (for get_authors)

  • authorId - Unique author identifier
  • name - Author's name
  • affiliations - Institutional affiliations
  • citationCount - Total citation count
  • hIndex - h-index metric
  • paperCount - Number of papers published
  • url - Author's profile URL

Example Field Usage

Get basic paper information:

semantic-scholar-mcp tools search_paper "machine learning" --fields "paperId,title,year,citationCount"

Get detailed paper with author affiliations:

semantic-scholar-mcp tools get_paper "10.1038/nature12373" --fields "title,abstract,authors.name,authors.affiliations,journal,year"

Get comprehensive author information:

semantic-scholar-mcp tools get_authors "649def34f8be52c8b66281af98ae884c09aef38b" --fields "authorId,name,affiliations,citationCount,hIndex,paperCount"

Development

Setting up the development environment

uv sync

uv run pytest tests/
uv run ruff format .
uv run ruff check . --fix
uv run ty check

Project Structure

semantic-scholar-mcp/
  src/
    semantic_scholar_mcp/
      __init__.py
      server.py      # Main server implementation
      cli.py         # CLI interface
  tests/                 # Test files
  pyproject.toml        # Project configuration
  README.md            # This file

API Rate Limits

  • Without API key: 100 requests per 5 minutes
  • With API key: 1 request per second (higher limits available on request)

Supported Paper ID Types

The API supports various paper identifier formats:

  • Semantic Scholar ID (e.g., "649def34f8be52c8b66281af98ae884c09aef38b")
  • DOI (e.g., "10.1038/nature12373")
  • ArXiv ID (e.g., "arXiv:2106.15928")
  • MAG ID
  • ACL ID
  • PubMed ID
  • Corpus ID

License

MIT License

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Acknowledgments

This project uses the Semantic Scholar API to access academic paper data.