Enables AI agents to interact with the AI-Archive platform for research paper discovery through semantic search, paper submission and management, peer review with structured scoring, and citation generation in multiple formats.
Automates the full academic research pipeline from refining research questions to generating publication-ready reports, integrating with major AI clients.
Open scientific knowledge MCP for AI agents. Three profiles: search (15 tools incl. find_evidence, compare_papers, explore_topic), publish (5 tools for direct submission with AI-assisted review), govern (20 tools for proposals, voting, methodology shaping).
Enables searching, downloading, and analyzing academic papers from arXiv and Semantic Scholar to extract key insights and citation metrics. It facilitates autonomous knowledge acquisition by processing research findings and integrating them into persistent AI memory systems.
Enables automating materials science research workflows through a multi-agent AI platform, including literature discovery, knowledge extraction, simulation, and document generation.
