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CodeSentinel is a comprehensive code quality analysis server designed to act as a crucial quality gate for AI-generated code within the Model Context Protocol (MCP) ecosystem. Unlike traditional linters that focus on syntax and style, CodeSentinel employs a sophisticated pattern-based approach to detect semantically deceptive issues often introduced by AI coding assistants, such as hardcoded secrets, error-swallowing catch blocks, and placeholder implementations. It analyzes code across 93 distinct patterns in multiple languages, offering verification-aware detection, LLM-optimized structured JSON output, and balanced assessments that recognize both weaknesses and strengths to ensure code integrity before deployment.
