Semantic Scholar API: Search 200M+ Papers with AI-Powered Recommendations (Free Key)

Why Semantic Scholar? While OpenAlex and Crossref give you raw metadata, Semantic Scholar adds something they can't: AI-powered paper recommendations and TLDR summaries generated by their S2 models. Built by the Allen Institute for AI, it indexes 200M+ papers and provides: AI-generated TLDRs for papers Citation intent classification (is this paper supporting, contrasting, or just mentioning?) Paper recommendations ("papers like this one") Author disambiguation Free API key with 100 requests per 5 minutes Get Your Free API Key Go to semanticscholar.org/product/api Sign up (free) Get your API key Or use without a key (lower rate limits). Search Papers import requests API_KEY = " your-key-here " # Optional but recommended headers = { " x-api-key " : API_KEY } if API_KEY != " your-key-here " else {} def search ( query , limit = 5 ): resp = requests . get ( " https://api.semanticscholar.org/graph/v1/paper/search " , params = { " query " : query , " limit " : limit , " fields " : " title,yea