A Model Context Protocol server that enables querying the Crossref API to search for academic publications by title, author, or DOI, returning structured metadata about scholarly works.
"mcp\_scholar" is a Python-based tool for searching and analyzing Google Scholar papers, supporting features like keyword-based searches and integration with MCP clients and Cherry Studio. It provides functionalities such as fetching top-cited papers from scholar profiles and summarizing research top
Enables real-time search and retrieval of academic paper information from multiple sources, providing access to paper metadata, abstracts, and full-text content when available, with structured data responses for integration with AI models that support tool/function calling.
This project is a Model Context Protocol (MCP) server that fetches articles from GeekNews. It is implemented in Python, and performs web scraping using BeautifulSoup.