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.
Enables autonomous auditing of scientific papers for methodology flaws, identifying selection bias and p-hacking, while computing consensus ratios and verifying citation credibility through MCP-compliant tooling.
Enables decomposition of complex research queries into multi-hop sub-queries and synthesis DAGs, with scientific consensus analysis, citation credibility verification, and deterministic JSON outputs for MCP-compliant clients.
Provides advanced analytical, research, and natural language processing capabilities through a Model Context Protocol server, enabling dataset analysis, decision analysis, and enhanced NLP features like entity recognition and fact extraction.
Enables searching and accessing academic papers from 23+ sources (including arXiv, PubMed, Google Scholar) through the Model Context Protocol, with unified tools for search, download, and text extraction.
