Patent Literature Search MCP vs Semantic Scholar MCP

patsnap_search

Search either patents or scientific literature in a

patsnap_fetch

Retrieve a patent or literature record as Markdown using

semantic_scholar_search_papers

Search for academic papers. Relevance-ranked keyword search over 200M+ papers; supports boolean operators (AND, OR, NOT) and quoted phrases, plus year, field-of-study, publication-type, open-access, and citation-count filters. Page with offset/limit (max 100 per call). For sorted or very large result sets use semantic_scholar_bulk_search; to search inside paper full text use semantic_scholar_snippet_search; to resolve one known title use semantic_scholar_match_paper. Returns Markdown by default, response_format='json' for raw JSON.

semantic_scholar_get_paper

Get paper details. Accepts: S2 ID, DOI:xxx, ARXIV:xxx, PMID:xxx, CorpusId:xxx Returns title, abstract, authors, venue, year, citation counts, TLDR, and open-access PDF link for one paper, e.g. paper_id='ARXIV:1706.03762'. Set include_citations / include_references to also list citing and referenced papers (fetched in parallel, 1-100 each). Results are cached in memory for 5 minutes; an unknown ID raises a not-found error. Unkeyed requests are throttled to 1 req/s (10 req/s with SEMANTIC_SCHOLAR_API_KEY) and 429/502/503 responses retry automatically with backoff. Returns Markdown by default, response_format='json' for raw JSON. To fetch many papers at once use semantic_scholar_bulk_papers.