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 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 auditing scientific papers for methodological biases such as selection bias and p-hacking, and assessing citation credibility and research consensus.
Enables AI agents and LLM tools to verify academic citations against real literature, detect hallucinated references, retrieve authoritative metadata and DOIs, generate BibTeX/APA/IEEE citations, and search over 200M+ scientific publications via MCP tools.
Provides MCP tools to check reference lists for retracted or problematic citations, retrieve nuanced editorial statuses with evidence, and monitor institutions for newly flagged papers using open data from OpenAlex, Retraction Watch, and Crossref.
