Scientific Fraud Detection MCP

Example Use Cases

• 1

  Audit and verify the statistical consistency of scientific research data.

• 2

  Detect image manipulation and data forensics in academic publications.

• 3

  Identify citation manipulation and publication bias in research literature.

Description

This MCP server provides a suite of eight tools designed to identify various forms of scientific fraud, including statistical inconsistencies, p-hacking, publication bias, citation manipulation, and image/data manipulation. It supports recursive self-calibration to improve detection accuracy and traces contamination pathways from retracted papers. The server integrates with platforms like Claude Desktop, Cursor, and Windsurf, requiring an Apify API token for authentication. It is a valuable resource for maintaining scientific integrity and supporting peer review processes.