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Why this server?
A biomedical literature annotation and relationship mining server based on PubTator3, providing convenient access through the MCP interface.
Why this server?
Enables AI assistants to search and access medRxiv papers through a simple MCP interface.
Why this server?
MCP Extension that gives LLMs access to arXiv and Hugging Face papers, enabling users to discuss papers, search for new research, and organize literature reviews through natural conversation.
Why this server?
Server to search PubMed (PubMed is a free, online database that allows users to search for biomedical and life sciences literature).
Why this server?
An MCP server that enables language models to fetch protein information from the UniProt database, including protein details, sequences, functions, and structures.
Why this server?
A Model Context Protocol server that provides Claude and other LLMs with read-only access to Hugging Face Hub APIs, enabling interaction with models, datasets, spaces, papers, and collections through natural language.
Why this server?
An MCP server implementation that enables searching and retrieving research articles from PubMed with specific focus on open access content filtering and full-text link retrieval.
Why this server?
A server that allows AI assistants to search for research papers, read their content, and access related code repositories through the PapersWithCode API.
Why this server?
"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
Why this server?
Provides real-time access to academic paper information from multiple sources, enabling structured results while handling CAPTCHAs and simulating user browsing patterns.