#code-quality

Generates high-quality unit tests for Python code with a coverage before/after report on every run. Derives concrete edge cases (None inputs, numeric boundaries, empty collections, exception paths) and returns ready-to-run pytest files with external I/O automatically mocked. Free tier: 100 executions. Pro: $19/month.

AI Constraint Engine that enforces CLAUDE.md, .cursorrules, and AGENTS.md rules. 51 MCP tools, 991 tests.

Static code analyzer with MCP server. Gives AI agents access to complexity metrics, coupling analysis, community detection, risk scoring, and test quality, without reading every file.

Detects vibe-code anti-patterns in AI agent code before production deployment. AST-powered analysis for Python, JavaScript, and LLM prompts.

Reinforcement for AI-generated code. Enforcement hooks, quality audits, and compliance packs that prevent AI coding tools from shipping broken code.

Code intelligence MCP server that makes AI coding safer. Builds a dependency graph of your entire codebase so Claude, Cursor, or any MCP client knows what breaks before making changes. 60+ tools for impact analysis, health scoring, dead code detection, and architecture enforcement. Built for vibecoders who ship fast and teams who need reliability. Supports Python, TypeScript, JavaScript.

Deterministic quality gates for AI coding agents. Rigour runs 23 automated checks on every file AI writes — structural analysis, security scanning, AI-drift detection, and agent governance. Works as an MCP server for Claude Desktop, Cursor, and Cline. Supports TypeScript, JavaScript, Python, Go, Ruby, and C#. Forces AI agents to write production-grade code with PASS/FAIL enforcement.

Open Source AI Code Review

Kodus MCP HTTP server exposing OSV (v1) for open source vulnerability lookup via osv_query/osv_query_batch tools.

AI-Safe Code Analysis with 113+ MCP tools - guard, memory, workflow, testing, latent chain

Educational Python refactoring assistant with guided suggestions for AI assistants

Educational Python refactoring assistant with guided suggestions for AI assistants

Stop AI coding disasters before they cost you weeks. Real-time anti-pattern detection for vibe coders who love AI tools but need a safety net to avoid expensive overengineering traps.

AI-powered code quality analysis using MCP to help AI assistants review code more effectively. Analyze git changes for complexity, security issues, and more through structured prompts.

MCP server for analyzing code for bugs, errors, and functionality issues

A Model Context Protocol (MCP) server for analyzing GitLab repositories and performing security assessments.