Enables automated scientific paper analysis, citation credibility verification, consensus ratio calculation, and multi-hop research queries through the Model Context Protocol, integrating with MCP-compliant clients.
A comprehensive Model Context Protocol server that provides AI assistants with direct access to Semantic Scholar's academic database, enabling advanced paper discovery, citation analysis, author research, and AI-powered recommendations.
Provides real-time access to over 200 million scientific papers and full-text extraction from major academic sources including arXiv, OpenAlex, and PubMed Central. It enables users to search, fetch metadata, and analyze citations across multiple research disciplines through a unified Model Context Protocol interface.