Scientific Papers
Empowers Large Language Models with real-time access to scientific papers from arXiv and OpenAlex.
About
Scientific Papers is a Model Context Protocol (MCP) server designed to bridge the gap between large language models (LLMs) and the vast world of scientific literature. It provides LLMs with real-time, structured access to papers from leading academic repositories like arXiv and OpenAlex, enabling advanced functionalities such as fetching the latest research, extracting full text content, analyzing citations, and looking up specific articles by ID. This tool is crucial for building intelligent agents that can conduct scientific research, summarize complex papers, or stay updated with cutting-edge advancements.
Key Features
- Fetch latest papers by category/concept from arXiv and OpenAlex
- Extract full text content from scientific paper HTML sources
- Identify top cited papers from OpenAlex since a specific date
- Retrieve full metadata for specific papers by ID
- Respectful API usage with per-source rate limiting
- 1 GitHub stars
Use Cases
- Provide LLMs with real-time access to scientific papers for research and analysis.
- Automate the discovery and summarization of new research in specific academic fields.
- Enhance AI agents with the ability to answer complex scientific queries using up-to-date literature.
Sponsored