GitKraken Desktop Download

GitKraken Desktop does not provide in-editor AI code completion, but it does support Copilot CLI as a coding agent. Its primary role is helping developers manage Git repositories, branches, commits, pull requests, and connections to Git hosting services.

If you use GitHub Copilot, you’ll typically run it inside a code editor such as Visual Studio Code. GitKraken Desktop and Copilot can still be used together in the same development process: Copilot can assist while you write code, while GitKraken Desktop helps you manage the Git side of your workflow.

GitKraken AI adds AI-assisted workflows directly inside GitKraken Desktop. It is designed to help with common Git tasks such as drafting commit messages, summarizing pull requests, explaining commits, creating stash messages, and resolving merge conflicts with suggested resolutions.

Because these capabilities are built into GitKraken Desktop, you do not need to move between separate tools or copy content into an external AI assistant. To use GitKraken AI, look for the ✨ icon near supported commit, pull request, stash, or merge actions.

GitKraken AI includes:

• Commit Composer
• AI-generated commit messages
• AI-assisted merge conflict resolution
• AI-generated pull request titles and descriptions
• AI-generated stash messages
• AI commit explanations

Your free trial of GitKraken Desktop gives you access to everything in our Pro plan. This includes 1,000,000 AI credits per week per user (trials are free for 2 weeks).

AI credit usage resets weekly on Sundays (UTC). Each Sunday marks the beginning of a new reporting week. Note: unused credits do not roll over.

GitKraken Pro includes advanced features for developers and teams that need more control over their Git workflow. Pro features include access to private repositories, cloud issue tracker integrations, conflict prevention, Launchpad, Cloud Patches, multiple profiles, and timely email support from the GitKraken team.

With GitKraken Pro, you can:

1. Access private repositories hosted on remote Git providers.
2. Connect cloud issue trackers such as Jira Cloud and Trello.
3. Use conflict prevention to spot potential merge conflicts before they become blockers.
4. Manage pull requests and issues from Launchpad.
5. Create and share Cloud Patches without opening a pull request.
6. Switch between multiple profiles with different Git configurations and app settings.

To start using these features, open a private repository in GitKraken Desktop, visit the Launchpad tab for pull requests and issues, or go to the Integrations area to connect supported issue trackers. For Cloud Patches, refer to the Cloud Patches documentation for setup and sharing steps.

GitKraken Desktop generally supports integrations with self-hosted Git services on Advanced plans and higher, including GitHub Enterprise, GitLab Self-Managed, Bitbucket Data Center, and Azure DevOps. GitLab Self-Managed is available on our Pro plan, however.

To connect a self-hosted Git provider, first create a Personal Access Token, or PAT, from your Git server. The token must include the permissions required by that provider. For example, GitLab Self-Managed commonly requires scopes such as api and read_user.

In GitKraken Desktop, open Preferences, go to Integrations, choose your self-hosted provider, enter the host domain, and paste the token when prompted.

For full setup details, visit the GitKraken documentation for integrations with Git providers.

Yes. GitKraken Desktop On-Premise is available for teams that need to keep Git workflows within their own infrastructure.

There are two On-Premise deployment options: a Self-Hosted Server option that runs with Docker on Linux, and a Serverless option activated with a license file. Both On-Premise options are sold separately from standard GitKraken subscriptions.

Visit the On-Premise Pricing page for details.

Yes. GitKraken AI workflows can be used in an On-Premise environment when connected to an approved internal large language model. Supported AI-assisted workflows include commit message generation, pull request descriptions, and merge conflict resolution.

On-Premise AI can connect to approved internal LLM options such as Azure OpenAI, Anthropic, or a locally hosted model like Ollama.

In this setup, code and metadata remain inside your network.