Claude Sycophancy Detector MCP Connector for Claude
A+Detects when AI models agree with incorrect user assumptions by verifying factual claims against codebase metadata.
The Claude Sycophancy Detector is a diagnostic tool designed to identify sycophantic behavior in AI models. Sycophancy occurs when an AI prioritizes user agreement over factual accuracy, often validating incorrect assumptions or non-existent code structures. This MCP server provides tools to extract factual claims--such as file paths, function signatures, and variable names--from an AI response and validate them against a provided ground truth codebase metadata. By using analyze_response_accuracy, users can calculate a factual accuracy ratio and a sycophancy risk score. The extract_claims_from_text tool isolates specific assertions, while get_sycophancy_risk_summary provides human-readable risk levels and actionable recommendations. This tool is essential for ensuring the reliability of AI-driven code analysis in Cursor, VS Code, Claude Desktop, and Windsurf.
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