# Semantic Scholar API: Get paper details > Finds a paper on Semantic Scholar by title, DOI or Semantic Scholar link and returns its abstract, one-sentence summary, authors, publication details, citation counts and a free PDF link when there is one. Unofficial. Not affiliated with or endorsed by Semantic Scholar. - Page: https://fous.com/methods/semanticscholar.org/get-paper - Method: `semanticscholar.org/get_paper`, version 1 - Website: semanticscholar.org - Returns: title, abstract, TLDR, authors, year, publication date, venue, fields of study, citation counts, free PDF link, DOI, Semantic Scholar link - Effect: read (it gets data and changes nothing) - Sign-in: none needed - Cost: 1 credit per completed run (1¢ with pay as you go); failed runs are free - Verified: Nov 2, 2026 ## Inputs | Field | Type | Required | In the run below | Description | |---|---|---|---|---| | `paper` | string | yes | `"https://www.semanticscholar.org/paper/204e3073870fae3d05bcbc2f6a8e263d9b72e776"` | Paper title, DOI, or Semantic Scholar paper link; for example, BERT: Pre-training of Deep Bidirectional Transformers. | ## Output From a run on Oct 31, 2026, shortened. Its input: ```json { "paper": "https://www.semanticscholar.org/paper/204e3073870fae3d05bcbc2f6a8e263d9b72e776" } ``` Its output: ```json { "doi": null, "tldr": "A new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely is proposed, which generalizes well to other tasks by applying it successfully to English constituency parsing both with large and limited training data.", "year": 2017, "title": "Attention is All you Need", "venue": "Neural Information Processing Systems", "authors": [ "Ashish Vaswani", "Noam Shazeer", "Niki Parmar" ], "abstract": "The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration. The best performing models also connect the encoder and decoder through an attention mechanism. We propose a new simple network architecture, the Transformer…", "paper_link": "https://www.semanticscholar.org/paper/204e3073870fae3d05bcbc2f6a8e263d9b72e776", "free_pdf_link": "https://arxiv.org/pdf/1706.03762.pdf", "citation_count": 194179, "fields_of_study": [ "Computer Science" ], "reference_count": 41, "publication_date": "2017-06-12", "semantic_scholar_paper_id": "204e3073870fae3d05bcbc2f6a8e263d9b72e776", "influential_citation_count": 20803 } ``` ## Run it From code, with a Fous API key in `FOUS_API_KEY`; the answer's `data` holds the output: ```bash curl https://api.fous.com/v1/runs \ -H "Authorization: Bearer $FOUS_API_KEY" \ -H "Content-Type: application/json" \ -d '{"method":"semanticscholar.org/get_paper","input":{"paper":"https://www.semanticscholar.org/paper/204e3073870fae3d05bcbc2f6a8e263d9b72e776"}}' ``` From an AI agent connected to the Fous MCP server: its `run` with the same method and input. To connect one, give it `set up https://fous.com/SKILL.md`. ## Ask your agent - Can you pull up the abstract and citation count for "Attention Is All You Need" on Semantic Scholar? - I need the authors, venue and publication year for the paper with DOI 10.1038/s41586-021-03819-2 - Is there a free PDF of "Deep Residual Learning for Image Recognition"? Also give me a one-line summary of it. - Look up this Semantic Scholar link and tell me what the paper is about and how many times it's been cited: https://www.semanticscholar.org/paper/204e3073870fae3d05bcbc2f6a8e263d9b72e776 - What fields of study and publication date are listed for "Language Models are Few-Shot Learners"? Get me its DOI too. ## Input schema ```json { "type": "object", "required": [ "paper" ], "properties": { "paper": { "type": "string", "minLength": 1, "description": "Paper title, DOI, or Semantic Scholar paper link; for example, BERT: Pre-training of Deep Bidirectional Transformers." } } } ``` ## Output schema ```json { "type": "object", "required": [ "title", "abstract", "tldr", "authors", "year", "publication_date", "venue", "fields_of_study", "citation_count", "influential_citation_count", "reference_count", "free_pdf_link", "doi", "paper_link", "semantic_scholar_paper_id" ], "properties": { "doi": { "type": [ "string", "null" ], "description": "Digital object identifier." }, "tldr": { "type": [ "string", "null" ], "description": "One-sentence paper summary." }, "year": { "type": [ "integer", "null" ], "description": "Publication year." }, "title": { "type": "string", "description": "Paper title." }, "venue": { "type": [ "string", "null" ], "description": "Publication venue." }, "authors": { "type": "array", "items": { "type": "string" }, "description": "Author names." }, "abstract": { "type": [ "string", "null" ], "description": "Paper abstract." }, "paper_link": { "type": "string", "description": "Semantic Scholar paper page." }, "free_pdf_link": { "type": [ "string", "null" ], "description": "Link to a free PDF, if available." }, "citation_count": { "type": [ "integer", "null" ], "description": "Number of citations." }, "fields_of_study": { "type": "array", "items": { "type": "string" }, "description": "Fields of study." }, "reference_count": { "type": [ "integer", "null" ], "description": "Number of references." }, "publication_date": { "type": [ "string", "null" ], "description": "Publication date (YYYY-MM-DD)." }, "semantic_scholar_paper_id": { "type": "string", "description": "Semantic Scholar paper ID.", "x-fous-developer": true }, "influential_citation_count": { "type": [ "integer", "null" ], "description": "Number of influential citations." } }, "additionalProperties": false } ``` ## See more - [Semantic Scholar API: Search papers](https://fous.com/methods/semanticscholar.org/search-papers.md): Searches Semantic Scholar for research papers in relevance order, with field of study, year range and open-access filters, returning AI one-sentence summaries, citations and free PDF links when available. - [Semantic Scholar API: Get researcher impact metrics](https://fous.com/methods/semanticscholar.org/get-author.md): Finds a Semantic Scholar author by name (optionally limited to a listed institution), picks the best-cited matching profile and returns their impact metrics and up to 10 most-cited papers. - [arXiv API: Get paper](https://fous.com/methods/arxiv.org/get-paper.md): Gets an arXiv paper's title, authors, abstract, subjects, submission dates and publication details from its exact title, arXiv link or number. - [NIH API: Get PubMed article](https://fous.com/methods/pubmed.ncbi.nlm.nih.gov/get-article.md): Gets the full PubMed abstract and publication details for one article by title, PubMed link, or PubMed number (PMID). A title is searched in PubMed titles first and must closely match a found article. Some articles have no abstract or free full text. - [Unpaywall API: Get free version of a paper](https://fous.com/methods/unpaywall.org/get-free-version.md): Finds a legal free copy of a paper by title or DOI, with its best available link and other copies. If no free copy is indexed, the copy links are null. - [OpenAlex API: Search scholarly papers](https://fous.com/methods/openalex.org/search-papers.md): Searches OpenAlex scholarly works by topic, with optional institution, publication-year and open-access filters, ranked by relevance, citations or newest date. - [arXiv API: Search papers](https://fous.com/methods/arxiv.org/search-papers.md): Finds arXiv preprints by topic or title words, with optional author, subject, submission date range and sorting. Returns up to 100 papers with abstracts, subjects, dates and links. - [Google API: Get patent details](https://fous.com/methods/patents.google.com/get-patent.md): Gets one public patent or published application by number, title, or Google Patents link, with claims, citations, family and classifications. - [All Semantic Scholar methods](https://fous.com/methods/semanticscholar.org.md)