This ArXiv MCP server, developed by blazickjp, provides an interface for AI assistants to search and analyze academic papers from the arXiv repository. It enables precise querying with filters like date ranges and categories, as well as full-text access to papers. Built with an asynchronous architecture in Python, the implementation handles paper downloads, local caching, and exposes a standardized MCP interface. By bridging AI models and academic literature, this server allows AI systems to engage deeply with scientific research in fields like computer science and physics. It is particularly useful for AI assistants needing to conduct literature reviews, answer technical questions, or provide summaries of recent developments in specific research areas.
blazickjp