Guide

AI Code Review Tools Directory

A hub for AI code review: automated PR feedback, code quality checks, and tools that integrate with GitHub, GitLab, and your workflow.

By AI Coding Tools Directory•2026-02-28•8 min read
Last reviewed: 2026-02-28
ACTD
AI Coding Tools Directory

Editorial Team

The AI Coding Tools Directory editorial team researches and reviews AI-powered development tools to help developers find the best solutions for their workflows.

AI code review tools automate first-pass analysis of pull requests. This directory links to tools, guides, and comparisons so you can choose the right fit.

Quick Answer

AI code review = automated analysis of PRs for bugs, style, security, and clarity. Top tools: CodeRabbit, GitHub Copilot (Business+), Qodo. Browse our Code Review collection and read the AI code review tools guide for a full overview.

Tools in This Cluster

Tool Focus Best for
CodeRabbit GitHub-native PR review Teams on GitHub
GitHub Copilot Completions + PR review Copilot subscribers
Qodo Code quality, review Dedicated review workflow

Full list: Code Review collection.

Related Guides

When AI Review Helps

Good fit Less critical
High PR volume Small teams with thorough review
Junior-heavy teams Strict compliance, human-only required
Catching common bugs Architectural decisions

How to Choose

  1. Platform: GitHub, GitLab, or both?
  2. Integration: Standalone app vs built into your IDE?
  3. Compliance: Data handling, self-hosted options?
  4. Cost: Free tier vs paid per seat?

Related in This Cluster

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Tools Mentioned in This Article

CodeRabbit

AI-powered code review for GitHub and GitLab pull requests

Freemium
→

Cursor

The AI-native code editor with $1B+ ARR, 25+ models, and background agents on dedicated VMs

Freemium
→

GitHub Copilot

AI pair programmer built into GitHub and popular IDEs

Freemium
→

Qodo

AI test generation and PR review (formerly CodiumAI)

Contact-sales
→

Workflow Resources

Cookbook

AI-Powered Code Review & Quality

Automate code review and enforce quality standards using AI-powered tools and agentic workflows.

Cookbook

Building AI-Powered Applications

Build applications powered by LLMs, RAG, and AI agents using Claude Code, Cursor, and modern AI frameworks.

Cookbook

Building APIs & Backends with AI Agents

Design and build robust APIs and backend services with AI coding agents, from REST to GraphQL.

Cookbook

Debugging with AI Agents

Systematically debug complex issues using AI coding agents with structured workflows and MCP integrations.

Skill

Change risk triage

A systematic method for categorizing AI-generated code changes by blast radius and required verification depth, preventing high-risk changes from shipping without adequate review.

Skill

Configuring MCP servers

A cross-tool guide to setting up Model Context Protocol servers in Cursor, Claude Code, Codex, and VS Code, including server types, authentication, and common patterns.

Skill

Local model quality loop

Improve code output quality when using local AI models by combining rules files, iterative retries with error feedback, and test-backed validation gates.

Skill

Plan-implement-verify loop

A structured execution pattern for safe AI-assisted coding changes that prevents scope creep and ensures every edit is backed by test evidence.

MCP Server

AWS MCP Server

Open source MCP servers from AWS Labs that give AI coding agents access to AWS documentation, best practices, and contextual guidance for building on AWS.

MCP Server

Docker MCP Server

Docker MCP Gateway orchestrates MCP servers in isolated containers, providing secure discovery and execution of Model Context Protocol servers across AI coding tools.

MCP Server

Figma MCP Server

Official Figma MCP server that brings design context, variables, components, and Code Connect data into AI coding sessions for design-to-code workflows.

MCP Server

Firebase MCP Server

Experimental Firebase MCP server that gives AI coding agents access to Firestore, Auth, security rules, Cloud Messaging, and project management through the Firebase CLI.

Frequently Asked Questions

What are AI code review tools?
Tools that use AI to analyze pull requests: suggest fixes, flag bugs, check style, and explain changes. They augment human review rather than replacing it.
Which AI code review tool is best?
CodeRabbit is popular for GitHub-native review. Copilot includes review in Business/Enterprise. Qodo offers dedicated review. Compare by your stack and workflow in our [Code Review collection](/collections/code-review).
Are AI code review tools free?
Some have free tiers; Copilot and others include review in paid plans. Enterprise tools often require a contract. See individual tool pages for current pricing.
Can AI code review replace human reviewers?
No. Use AI for triage, common issues, and explanations. Humans should handle architecture, context, and final approval.

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