Empower AI agents to autonomously search, analyze, and explore academic papers from arXiv. This tool provides a comprehensive suite of features, including advanced multi-field search, author-specific queries, category browsing, version tracking, citation extraction, and related paper discovery, all accessible through a Model Context Protocol (MCP) server. It further enhances research workflows with AI-powered prompts for literature reviews, research gap identification, paper comparison, and trend analysis, making it an indispensable resource for automated academic research.
Key Features
01Advanced multi-field search with date ranges and sorting options
02Author-specific searches with affiliation tracking
03Category browsing for all ArXiv subject areas
04Citation extraction from abstracts and metadata
05AI-powered prompts for literature reviews and trend analysis
060 GitHub stars
Use Cases
01Conduct advanced searches for academic papers based on authors, keywords, dates, and categories.
02Analyze papers by extracting citations, tracking versions, and discovering related research.
03Generate research insights like literature reviews, identify research gaps, and compare multiple papers.
