Enables users to search and analyze academic papers from multiple sources, fetch metadata and full text, and build structured outputs like literature maps and paper comparisons.
Enables agents to search papers across Semantic Scholar and arXiv, read and extract text from arXiv PDFs, align records across sources, and produce structured literature-analysis digests.
Enables AI agents to search scholarly works, authors, institutions, venues, and concepts, retrieve detailed metadata, and explore citation networks through natural-language requests.
Enables AI agents to search and retrieve academic papers from arXiv and PubMed with citation-grade extraction, providing clean citations and summaries.
Enables discovery and analysis of research ecosystems by extracting metadata from paper URLs, GitHub repositories, and research names. Automatically finds related papers, code repositories, models, datasets, and authors across platforms like arXiv, HuggingFace, and GitHub.
Enables arXiv paper search, PDF download, text extraction, and context chunking for LLM pipelines, along with advanced features like citation graphs and reproducibility scoring.