CodeRabbit GitLab Integration: Step-by-Step Configuration (2026)

Why integrate CodeRabbit with GitLab

GitLab teams face the same code review bottlenecks as everyone else - but with fewer AI review tool options. Most AI code review tools launched with GitHub-first support, leaving GitLab users waiting months or years for equivalent integrations. CodeRabbit is one of the few AI review tools that provides full-featured support for GitLab, including automated merge request analysis, inline review comments, and interactive conversations - all working the same way they do on GitHub.

If your team uses GitLab for source control and CI/CD, integrating CodeRabbit means every merge request gets instant AI-powered feedback covering bugs, security vulnerabilities, performance issues, and logic errors. Developers get actionable review comments within minutes of pushing code instead of waiting hours for a human reviewer to become available. The result is faster review cycles, fewer defects reaching production, and senior engineers spending less time on routine code review tasks.

The CodeRabbit GitLab integration connects through OAuth and webhooks rather than a native marketplace app like on GitHub. This means the setup process has a few more steps, but the end result is functionally identical. Every feature available on GitHub - including .coderabbit.yaml configuration, path-specific review instructions, the knowledge base, and interactive chat - works on GitLab without limitations.

This guide walks through the complete setup process from start to finish, including prerequisites, GitLab OAuth configuration, project selection, merge request review behavior, .coderabbit.yaml configuration, troubleshooting, and how CodeRabbit fits into your existing GitLab CI/CD pipeline.

Prerequisites for CodeRabbit GitLab integration

Before starting the integration, confirm you have the following in place.

You need a GitLab account on either GitLab.com (SaaS) or a self-managed GitLab instance. CodeRabbit supports both, though self-managed instances require the Enterprise plan and some additional network configuration. For this guide, we will focus on GitLab.com, which works with all CodeRabbit plans including the free tier.

You need Maintainer or Owner role on the GitLab projects where you want CodeRabbit to review merge requests. This permission level is required because CodeRabbit needs to create webhooks on your projects during setup. If you are a Developer-level member, you will need to ask a Maintainer or Owner to either complete the setup or temporarily elevate your permissions.

You need at least one GitLab project with an active merge request or the ability to create one for testing. While not strictly required for setup, having a test MR ready lets you verify the integration is working immediately after configuration.

No other prerequisites exist. CodeRabbit does not require you to modify your .gitlab-ci.yml pipeline configuration, install any runners, set up API tokens manually, or install local tooling. The entire setup happens through the browser.

Step 1: Create your CodeRabbit account with GitLab

Start by signing up for CodeRabbit using your GitLab identity.

1. Open coderabbit.ai in your browser
2. Click the “Get Started Free” button on the homepage
3. Select GitLab as your Git platform from the available options (GitHub, GitLab, Azure DevOps, Bitbucket)
4. GitLab displays its standard OAuth authorization page asking you to grant CodeRabbit specific permissions

The OAuth prompt shows exactly what CodeRabbit is requesting access to. Review these permissions before clicking “Authorize”:

• Read access to your profile - CodeRabbit needs your identity to create your account
• Read access to repository contents - required to analyze merge request diffs in the context of the full codebase
• Read and write access to merge requests - required so CodeRabbit can read MR details and post review comments as discussion threads
• Webhook management - required to create webhooks that notify CodeRabbit when merge requests are opened or updated

Click “Authorize” to complete the OAuth flow. GitLab redirects you back to the CodeRabbit dashboard where your account is now created and linked to your GitLab identity.

The free tier requires no credit card. It covers unlimited public and private repositories with AI-powered MR summaries and review comments. Rate limits of 200 files per hour and 4 MR reviews per hour apply on the free plan, but these are sufficient for most small to mid-size teams.

For teams already using CodeRabbit on GitHub, you can connect your GitLab account to the same CodeRabbit organization. This is useful for teams that use both platforms across different projects.

Step 2: Select GitLab groups and projects

After authentication, configure which GitLab projects CodeRabbit should monitor.

1. From the CodeRabbit dashboard, navigate to the “Repositories” or “Projects” section
2. CodeRabbit displays all GitLab groups and projects accessible to your account
3. Select the groups or individual projects you want to enable for AI code review
4. For each enabled project, CodeRabbit automatically creates a webhook that listens for merge request events

You have two approaches for selecting projects:

Group-level enablement - Select an entire GitLab group to enable CodeRabbit on all projects within that group, including any projects added to the group in the future. This is the fastest way to roll out CodeRabbit across an organization but means every project gets reviewed immediately.

Project-level enablement - Select individual projects one at a time. This gives you granular control and is the recommended approach for teams that want to pilot CodeRabbit on a few projects before expanding. Start with one or two projects that have active merge request activity.

For each enabled project, you can configure basic settings in the CodeRabbit dashboard:

• Review language - the language CodeRabbit writes its comments in (defaults to English, supports 20+ languages)
• Auto-review - whether CodeRabbit reviews MRs automatically on creation and update, or only when explicitly requested via @coderabbitai review
• Draft MR handling - whether to review MRs marked as Draft or WIP (defaults to skip)

After selecting your projects, CodeRabbit is ready to start reviewing merge requests. The webhooks are created automatically - you do not need to manually configure webhook URLs or secret tokens in your GitLab project settings.

Step 3: Verify the webhook configuration

Confirm that CodeRabbit’s webhook is properly installed on your GitLab projects.

While CodeRabbit creates webhooks automatically, it is good practice to verify the configuration, especially if you are working with self-managed GitLab instances or projects with custom webhook policies.

1. Open your GitLab project in the browser
2. Navigate to Settings > Webhooks in the left sidebar
3. Look for a webhook with a URL pointing to CodeRabbit’s endpoint (typically https://webhook.coderabbit.ai/gitlab or a similar URL)
4. Verify the webhook is configured to trigger on these events:
   • Merge request events - this is the primary trigger for code review
   • Note events - this allows CodeRabbit to respond when developers reply to its comments

If the webhook is missing or shows errors, you can manually recreate it:

1. In the CodeRabbit dashboard, navigate to the project settings
2. Copy the webhook URL and secret token provided by CodeRabbit
3. In GitLab, go to Settings > Webhooks and click “Add new webhook”
4. Paste the webhook URL, add the secret token, and select the merge request and note event triggers
5. Click “Add webhook” and test it using the “Test” button to verify connectivity

The webhook test should return a 200 OK response. If it returns an error, check that your GitLab instance can reach CodeRabbit’s servers over HTTPS. Self-managed GitLab instances behind firewalls may need to allowlist CodeRabbit’s IP ranges.

Step 4: Trigger your first merge request review

Open a merge request to see CodeRabbit’s GitLab integration in action.

1. Create a new branch in one of your enabled GitLab projects
2. Make a code change - even a small one like adding a function, fixing a bug, or refactoring a method
3. Push the branch to GitLab
4. Create a merge request targeting your default branch (usually main or master)
5. Wait 1 to 5 minutes for CodeRabbit to complete its review

CodeRabbit posts its feedback as GitLab discussion threads on the merge request. You will see:

• A walkthrough summary as the first comment on the MR, describing what changed across all files organized by file and purpose. This summary appears in the MR discussion timeline.
• Inline discussion threads on specific lines of code where CodeRabbit identifies potential issues, improvements, or suggestions. These threads appear in the “Changes” tab of the MR, attached to the relevant lines in the diff.
• A review status indicating whether the review is complete and how many comments were generated

Here is what a typical CodeRabbit review looks like on a GitLab merge request:

## Walkthrough
This MR adds rate limiting to the authentication API endpoints.
The `loginHandler` and `registerHandler` functions now check
a Redis-backed rate limiter before processing requests. Failed
attempts are tracked per IP address with a configurable window.

## Changes
| File | Change Summary |
|------|---------------|
| src/api/auth.go | Added rate limiter middleware and IP extraction |
| src/config/limits.go | New rate limit configuration struct and defaults |
| tests/api/auth_test.go | Four new test cases for rate limiting behavior |

Inline comments appear as resolvable discussion threads in the diff view. Each comment includes a description of the issue, an explanation of why it matters, and often a suggested fix. Developers can resolve individual threads as they address each finding, just like they would with comments from a human reviewer.

If CodeRabbit does not post any comments within 5 minutes, jump to the troubleshooting section later in this guide.

Step 5: Configure review behavior with .coderabbit.yaml

The .coderabbit.yaml file controls how CodeRabbit reviews your merge requests. This configuration file works identically on GitLab and GitHub, so if you are already familiar with how to use CodeRabbit, the same settings apply.

Create a file named .coderabbit.yaml in the root of your GitLab repository on the default branch:

# .coderabbit.yaml - works on both GitLab and GitHub
language: en-US

reviews:
  profile: chill
  request_changes_workflow: false
  high_level_summary: true
  poem: false
  review_status: true
  collapse_walkthrough: false
  sequence_diagrams: true
  changed_files_summary: true
  path_filters:
    - "!**/*.lock"
    - "!**/*.generated.*"
    - "!**/dist/**"
    - "!**/node_modules/**"
    - "!**/vendor/**"
    - "!**/coverage/**"
    - "!**/__snapshots__/**"
  path_instructions:
    - path: "src/api/**"
      instructions: |
        Review API endpoints for:
        - Input validation on all parameters
        - Proper error handling with appropriate status codes
        - Authentication and authorization checks
    - path: "src/db/**"
      instructions: |
        Review database code for:
        - SQL injection prevention
        - Proper connection handling and cleanup
        - Transaction usage for multi-step writes

chat:
  auto_reply: true

knowledge_base:
  opt_out: false
  learnings:
    scope: auto

Commit and push this file to your default branch. CodeRabbit reads the configuration from the default branch on every merge request, so changes take effect immediately without any restart or reauthorization.

Key configuration options for GitLab teams

profile determines how verbose CodeRabbit’s reviews are:

• chill - Fewer comments focused on bugs, security vulnerabilities, and logic errors. Best for teams new to AI code review who want to avoid overwhelming developers with feedback.
• assertive - More thorough reviews covering style, naming, documentation, and best practices alongside bugs. Best for teams that want comprehensive feedback on every MR.
• followup - Like assertive, but also checks whether findings from previous reviews were addressed in subsequent commits. Best for teams that want accountability.

path_filters controls which files CodeRabbit analyzes. The vendor/ exclusion is particularly relevant for GitLab teams working with Go projects, Ruby projects, or any language where vendored dependencies are committed to the repository.

path_instructions provides natural language instructions for specific directories. This is where the real customization power lives. You can tell CodeRabbit to focus on authentication in your API layer, check for SQL injection in database code, and validate test coverage in test files - all automatically applied to the right files in every MR.

Step 6: Interact with CodeRabbit on GitLab merge requests

CodeRabbit is conversational - every comment it posts is the start of a dialogue. On GitLab, interactions happen through merge request discussion threads.

Replying to review comments

When CodeRabbit posts an inline comment on your MR, reply to the discussion thread just like you would reply to a human reviewer:

• Ask for clarification: “Why is this a problem? We handle this case in the middleware layer.”
• Request an alternative: “This would break backward compatibility. Can you suggest an approach that maintains the existing API contract?”
• Accept and request the fix: “Good catch. Can you generate the fix?”

CodeRabbit reads your reply, understands the context of the conversation, and responds with a follow-up. It remembers the full discussion within the MR, so follow-up questions work naturally.

Using command keywords on GitLab

Post these commands as comments on your MR to control CodeRabbit’s behavior:

Command	What it does
@coderabbitai review	Triggers a full re-review of the MR
@coderabbitai resolve	Dismisses a specific review comment
@coderabbitai explain	Provides a detailed explanation of a finding
@coderabbitai generate docstring	Generates documentation for the function in context
@coderabbitai configuration	Shows the current configuration for the project
@coderabbitai help	Lists all available commands

These commands work in both the main MR discussion and inline discussion threads on specific lines of code.

Teaching CodeRabbit your team’s preferences

Every interaction with CodeRabbit trains it on your team’s conventions. When you dismiss a comment with an explanation (“We use dynamic types here intentionally because the schema comes from an external service”), CodeRabbit stores that as a learning and adjusts future reviews. Teams that actively engage with CodeRabbit during the first two weeks typically see a noticeable reduction in false positives by the end of the first month.

Step 7: Understand merge request analysis depth

CodeRabbit does not just look at the diff - it understands the context of your entire repository. This is what separates it from simple linting or pattern-matching tools.

When analyzing a GitLab merge request, CodeRabbit performs several layers of analysis:

Diff-level analysis examines every changed line for common issues like null pointer risks, missing error handling, resource leaks, race conditions, and security vulnerabilities. This is the most visible layer and produces the majority of inline comments.

Cross-file analysis looks at how changes in one file affect other files in the MR. If you modify a function signature in one file but do not update all call sites in another file within the same MR, CodeRabbit flags the inconsistency.

Repository-context analysis considers the broader codebase when reviewing changes. CodeRabbit understands how the changed code fits into the existing architecture, which means it can flag issues like introducing a new database query pattern that conflicts with the project’s established data access conventions.

Instruction-aware analysis applies the rules defined in your .coderabbit.yaml path instructions. When you tell CodeRabbit to focus on authentication checks in your API layer, it prioritizes those concerns when reviewing files matching the path pattern.

This multi-layer approach is why CodeRabbit catches issues that traditional static analysis tools miss. Tools like SonarQube and Semgrep apply fixed rules to individual files, which is excellent for deterministic bug detection. CodeRabbit applies contextual understanding to the entire changeset, catching logic errors and design problems that no rule could encode. For a deeper look at CodeRabbit’s capabilities, see our CodeRabbit review.

Step 8: Integrate CodeRabbit alongside GitLab CI/CD

CodeRabbit operates independently of your GitLab CI/CD pipeline, but the two complement each other well. Understanding how they work together helps you build a comprehensive code quality workflow.

How CodeRabbit fits into the MR lifecycle

CodeRabbit triggers via webhooks, not via .gitlab-ci.yml pipeline jobs. This means:

• CodeRabbit starts its review as soon as the MR is opened or updated, in parallel with your CI/CD pipeline
• CodeRabbit does not consume your GitLab Runner minutes or resources
• CodeRabbit’s review is independent of pipeline pass/fail status
• CodeRabbit does not appear as a pipeline job or stage in your GitLab CI/CD visualization

This separation is intentional. AI-powered code review is advisory by nature, and running it outside the pipeline prevents it from blocking merges due to occasional false positives.

Complementing CodeRabbit with CI/CD pipeline stages

The strongest code quality setup combines CodeRabbit’s AI review with deterministic tools running in your CI/CD pipeline. Here is an example .gitlab-ci.yml that runs alongside CodeRabbit:

stages:
  - lint
  - test
  - security

lint:
  stage: lint
  script:
    - npm run lint
    - npm run format:check
  rules:
    - if: $CI_PIPELINE_SOURCE == "merge_request_event"

test:
  stage: test
  script:
    - npm run test:coverage
  coverage: '/Lines\s*:\s*(\d+\.?\d*)%/'
  rules:
    - if: $CI_PIPELINE_SOURCE == "merge_request_event"

semgrep:
  stage: security
  image: returntocorp/semgrep
  script:
    - semgrep ci
  variables:
    SEMGREP_RULES: "auto"
  rules:
    - if: $CI_PIPELINE_SOURCE == "merge_request_event"

In this setup:

• Your CI/CD pipeline handles linting, testing, and deterministic security scanning - things that need to produce pass/fail results and gate merges
• CodeRabbit handles AI-powered review covering logic errors, design issues, contextual bugs, and architectural concerns - things that benefit from natural language feedback

Both run in parallel on every merge request. Developers see pipeline status in the MR widget and CodeRabbit comments in the discussion threads. Neither blocks the other.

Using merge request approval rules with CodeRabbit

GitLab’s merge request approval rules let you require specific approvals before merging. While CodeRabbit does not currently act as an approver in GitLab’s approval system, you can use it alongside approval rules to ensure both human and AI review happen on every MR:

1. Set up approval rules requiring at least one human reviewer approval
2. Enable CodeRabbit for automated AI review
3. Optionally require all discussion threads to be resolved before merging (this ensures developers address CodeRabbit’s findings)

To require resolved discussions, go to your project’s Settings > Merge requests and enable “All threads must be resolved.”

Troubleshooting CodeRabbit GitLab integration

If CodeRabbit is not working as expected on GitLab, work through these issues in order.

CodeRabbit is not posting comments on merge requests

1. Check the webhook. Go to your GitLab project’s Settings > Webhooks and verify the CodeRabbit webhook exists and is configured for merge request events. Check “Recent events” for failed deliveries - a red status indicates the webhook is not reaching CodeRabbit’s servers.
2. Check project status in the dashboard. Log in to app.coderabbit.ai and verify the GitLab project is toggled on.
3. Check if the MR is a Draft or WIP. CodeRabbit skips draft merge requests by default. Either mark the MR as ready or configure CodeRabbit to review drafts in the dashboard settings.
4. Check path filters. If your .coderabbit.yaml excludes all paths that changed in the MR, CodeRabbit has nothing to review.
5. Check rate limits. On the free tier, you are limited to 4 MR reviews per hour. Additional reviews are queued until capacity is available.
6. Test the webhook manually. In GitLab’s webhook settings, use the “Test” dropdown and select “Merge request events” to send a test payload to CodeRabbit. A 200 response confirms connectivity.

Webhook delivery failures

If webhook deliveries are failing (shown as red in GitLab’s webhook recent events):

• 403 Forbidden - The webhook secret token may be incorrect. Delete the webhook and let CodeRabbit recreate it by toggling the project off and on in the CodeRabbit dashboard.
• 500 Internal Server Error - CodeRabbit’s servers may be experiencing temporary issues. Check status.coderabbit.ai for service status.
• Connection refused or timeout - Your GitLab instance cannot reach CodeRabbit’s servers. This is common with self-managed GitLab behind firewalls. Allowlist CodeRabbit’s webhook endpoint IP ranges.

Comments appear but are not relevant

1. Add path-specific instructions in .coderabbit.yaml to give CodeRabbit context about your codebase architecture
2. Reply to irrelevant comments explaining why they do not apply - CodeRabbit learns from corrections
3. Switch to the chill review profile if you are currently on assertive to reduce noise
4. Enable the knowledge base so CodeRabbit builds context about your project over time

OAuth token expiration

If CodeRabbit stops working after a period of inactivity, your GitLab OAuth token may have expired. Go to the CodeRabbit dashboard, navigate to your profile settings, and re-authorize the GitLab connection. This refreshes the token without requiring you to reconfigure any projects or webhooks.

Alternatives to CodeRabbit for GitLab AI code review

While CodeRabbit is the most widely adopted AI code review tool for GitLab, other options exist. Understanding the alternatives helps you make an informed decision for your team.

CodeAnt AI

CodeAnt AI is a Y Combinator-backed platform that combines AI code review with SAST, secret detection, infrastructure-as-code security scanning, and DORA metrics in a single tool. It supports GitLab alongside GitHub, Azure DevOps, and Bitbucket.

CodeAnt AI pricing starts at $24/user/month for the Basic plan (AI PR reviews, summaries, and auto-fix) and goes up to $40/user/month for the Premium plan that adds SAST, secret detection, IaC security, and DORA metrics dashboards. The Premium plan is particularly compelling for teams that want to consolidate multiple tools into one platform rather than running CodeRabbit alongside separate security scanning tools.

The key difference between CodeAnt AI and CodeRabbit is breadth versus depth. CodeAnt AI covers more ground by bundling code review with security and metrics, while CodeRabbit focuses exclusively on AI code review and does it with more depth - including features like interactive chat, learning from feedback, and 40+ built-in linters. For teams already running separate SAST tools in their GitLab CI/CD pipeline, CodeRabbit’s focused approach may be the better fit. For teams that want one platform to replace multiple tools, CodeAnt AI is worth evaluating.

For a broader comparison of available options, see our guide to CodeRabbit alternatives and the best AI code review tools.

GitLab built-in AI features

GitLab has been rolling out AI-powered features under the GitLab Duo umbrella, including Code Suggestions for code completion and AI-assisted merge request summaries. However, these features focus on code generation and MR summarization rather than comprehensive code review. As of early 2026, GitLab Duo does not provide the depth of review feedback that CodeRabbit delivers - it does not post inline comments identifying bugs, security issues, or logic errors across the full diff.

For teams on GitLab Ultimate, GitLab Duo is worth enabling alongside CodeRabbit since the two serve different purposes. GitLab Duo helps developers write code faster, while CodeRabbit reviews the code they wrote.

Advanced configuration for GitLab teams

Once the basic integration is working, these advanced configurations help you get more value from CodeRabbit on GitLab.

Review instructions for GitLab-specific patterns

GitLab projects often follow conventions that differ from GitHub projects. Add instructions that reflect your GitLab workflow:

reviews:
  instructions: |
    This project uses GitLab CI/CD with the following conventions:
    - All CI jobs are defined in .gitlab-ci.yml using include templates
    - Environment variables use CI_ prefix for GitLab-provided vars
    - Deployment happens through GitLab Environments
    - Review apps are created for every MR
    Focus on logic errors, security issues, and performance problems.
    Do not comment on formatting - that is handled by our CI lint stage.
  path_instructions:
    - path: ".gitlab-ci.yml"
      instructions: |
        Review CI/CD configuration for:
        - Security of variable handling (no secrets in plain text)
        - Proper use of rules and only/except directives
        - Efficient job dependencies and parallelization
    - path: "deploy/**"
      instructions: |
        Review deployment scripts for:
        - Rollback safety
        - Environment-specific configuration handling
        - Proper use of GitLab CI/CD variables

Configuring for GitLab monorepos

GitLab monorepos can use path instructions to apply different review criteria to each component:

reviews:
  path_instructions:
    - path: "services/backend/**"
      instructions: |
        Backend service using Go. Focus on:
        - Error handling patterns (wrap errors with context)
        - Goroutine safety and proper mutex usage
        - Database query optimization
    - path: "services/frontend/**"
      instructions: |
        Frontend app using React/TypeScript. Focus on:
        - Component re-render optimization
        - Proper TypeScript typing (no any)
        - Accessibility compliance
    - path: "infra/terraform/**"
      instructions: |
        Infrastructure as code. Focus on:
        - Security group rules and IAM policies
        - Resource naming conventions
        - State management safety

Setting up notifications

While CodeRabbit posts all its feedback directly on the GitLab merge request, you may want to route review activity to other channels. CodeRabbit supports integrations with Slack, Microsoft Teams, and other notification platforms:

integrations:
  slack:
    enabled: true
    channel: "#code-reviews"

This sends a summary notification to your Slack channel whenever CodeRabbit completes a review, including a link back to the GitLab MR. This is useful for team leads who want visibility into review activity without monitoring every individual MR.

Best practices for CodeRabbit on GitLab

Follow these practices to maximize the value of your CodeRabbit GitLab integration.

Start with one or two projects and expand gradually. Enable CodeRabbit on projects with active MR activity and developers who are open to trying AI review. Collect feedback for one to two weeks before expanding to additional projects. This avoids the common pitfall of rolling out to the entire organization before the configuration is tuned.

Use the chill profile initially and increase strictness later. The chill profile limits comments to significant issues like bugs and security vulnerabilities. Once the team trusts CodeRabbit’s feedback quality, switch to assertive for broader coverage. If you start with assertive, the volume of comments on day one may cause developers to tune out all automated feedback permanently.

Write descriptive MR titles and descriptions. CodeRabbit uses the MR title and description as context for its review. A title like “Update handler” gives CodeRabbit minimal context. A title like “Add rate limiting to login endpoint” combined with a description of the problem being solved helps CodeRabbit provide more targeted feedback.

Keep merge requests small. CodeRabbit provides better feedback on focused MRs with fewer than 400 lines of changes. Large MRs spanning thousands of lines across dozens of files produce less precise comments because the context window is spread thin. This is the same principle that makes human code review more effective on smaller changesets.

Reply to CodeRabbit’s comments rather than silently resolving them. Every reply - whether you agree, disagree, or ask for clarification - teaches CodeRabbit about your team’s preferences and conventions. Teams that actively engage during the first two weeks report significantly fewer false positives by the end of the first month.

Combine CodeRabbit with static analysis in your CI/CD pipeline. CodeRabbit catches contextual issues that rules cannot encode - logic errors, missing edge cases, architectural inconsistencies. Static analysis tools like Semgrep and SonarQube catch deterministic issues with zero false negatives - known vulnerability patterns, coding standard violations, complexity thresholds. Running both gives you comprehensive coverage. See our guide on how to set up CodeRabbit for more configuration details.

Review the CodeRabbit dashboard monthly. The dashboard provides metrics on review activity, common issue types, and resolution rates across all your GitLab projects. Use these insights to adjust your .coderabbit.yaml configuration, identify areas of your codebase that generate the most findings, and demonstrate the tool’s value to engineering leadership.

Summary

Setting up CodeRabbit’s GitLab integration takes under 15 minutes and delivers immediate value on every merge request. The process involves creating a CodeRabbit account with GitLab OAuth, selecting your projects, verifying the webhook configuration, and optionally customizing review behavior with .coderabbit.yaml. Once configured, CodeRabbit automatically reviews every merge request with the same depth and quality it provides on GitHub - including walkthrough summaries, inline discussion threads, interactive chat, and learning from your feedback over time.

The key to success is a gradual rollout. Start with one or two projects using the chill review profile, actively engage with CodeRabbit’s comments during the first two weeks, tune your .coderabbit.yaml based on real feedback, and then expand to additional projects. Combine CodeRabbit with static analysis tools in your GitLab CI/CD pipeline for comprehensive coverage that catches both contextual issues and deterministic rule violations.

For teams evaluating their options, CodeRabbit remains the most mature AI code review tool with GitLab support, having reviewed over 13 million merge requests and pull requests across more than 2 million connected repositories. Whether you are a small team on the free tier or an enterprise on a self-managed GitLab instance, the integration delivers the same core experience - instant, contextual, and continuously improving AI-powered code review on every merge request.