MCP Research Papers
Query 250M+ papers across arXiv, OpenAlex, Semantic Scholar, and PubMed using search_all_sources for merged results with AI TL;DRs, search_arxiv by category/author, and search_pubmed for biomedicine. Build citation graphs via build_citation_graph, extract PDFs with fetch_arxiv_pdf, spot gaps using find_research_gaps, and track trends with get_trending_topics—no API key needed. Researchers, PhD students, data analysts, and developers rely on it for literature reviews, citation tracing, and knowledge mapping.
Overview
MCP Research Papers provides AI assistants with instant, key-free access to arXiv preprints, OpenAlex's 250M+ scholarly works, Semantic Scholar's AI-enriched papers, and PubMed's 35M+ biomedical citations—all queried simultaneously via search_all_sources. Retrieve metadata, full-text PDFs via fetch_arxiv_pdf, citation graphs with Mermaid diagrams using build_citation_graph, and research gaps through find_research_gaps comparing topic trends across time windows. Track real-time publications from today across physics, AI, medicine, economics, and humanities without outdated training data limitations.
Key Capabilities
Search arXiv by keyword, author, title, abstract, or category (e.g., 'ti:transformer au:Hinton' via search_arxiv or cs.AI latest via get_arxiv_category), fetch full details with get_arxiv_paper, and extract PDF text page-by-page using fetch_arxiv_pdf. Query OpenAlex across all disciplines with search_openalex (filter by year or open-access), pull DOI metadata via get_paper_by_doi, author profiles with get_author_works (h-index and top papers), or yearly trends via get_trending_topics. Leverage Semantic Scholar for similar papers (get_similar_papers), references (get_paper_references with influential flags), and full citation graphs (build_citation_graph); add PubMed biomedical searches (search_pubmed with MeSH terms and trial filters).
Use Cases
Data scientists query search_arxiv('cat:cs.LG reinforcement learning') then fetch_arxiv_pdf to extract methods sections for model training. PhD students run find_research_gaps('quantum computing', current_year=2024) to spot declining topics for thesis proposals, cross-referencing with get_similar_papers and build_citation_graph. Developers monitor get_arxiv_category('cs.CV') daily for computer vision updates, while medical analysts search_pubmed('COVID-19[Title] Meta-Analysis') and aggregate via search_all_sources for comprehensive reviews with TL;DR summaries.
Who This Is For
Researchers conducting literature reviews and citation tracing, PhD students building bibliographies and identifying gaps, data analysts mapping knowledge graphs and trends, developers integrating real-time paper feeds into AI apps, science journalists verifying claims with primary sources, and biomedical teams accessing PubMed alongside multidisciplinary coverage.