GitLab MCP. Manage projects, issues, and pipelines from your chat.
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GitLab MCP Server connects your entire development ecosystem to your AI client. Use it to list projects, check CI/CD pipeline status, track open issues, and read file contents across your entire GitLab instance.
It lets your agent manage the full DevSecOps lifecycle—from initial issue creation to final deployment—all via natural conversation. It's your central hub for project metadata and code visibility.
What your AI agents can do
Create merge request
Requires title.
Create a new merge request
Create project issue
Opens a new issue in a specific GitLab project.
Get merge request
Use the IID (the MR number shown in the UI, not the internal ID).
Get details for a specific merge request
Retrieve configuration details and metadata for specific projects across your GitLab instance.
List, track, and programmatically create project issues and merge requests via chat commands.
Fetch a list of pipelines for a project, allowing you to check build and deployment status in real-time.
Read the actual contents of files within any repository, letting you understand code structure or documentation without navigating the UI.
Run global searches that pull results from projects, issues, and users across your entire GitLab setup.
Access detailed profile information for the authenticated user to check permissions or account context.
Ask AI about this MCP
Supported MCP Clients
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GitLab MCP Server: 12 Tools for DevSecOps
Use these tools to manage project metadata, track issues, and monitor CI/CD pipelines across your entire GitLab instance via natural conversation.
019e9a98create merge request
Requires title. Create a new merge request
019d75a5create project issue
Opens a new issue in a specific GitLab project.
019e9a98get merge request
Use the IID (the MR number shown in the UI, not the internal ID). Get details for a specific merge request
019d75a5get my gitlab profile
Retrieves the identity and profile details of the currently logged-in user.
019d75a5get project details
Fetches the configuration metadata for a specific GitLab project.
019d75a5get repository file
Reads the text content of a specified file within a repository.
019e9a98list branches
List all branches in a project repository
019d75a5list merge requests
Lists all open or merged merge requests for a project.
019d75a5list project forks
Lists all forks associated with a specific project.
019d75a5list project issues
Lists all open or closed issues for a project.
019e9a98list project members
List all members of a project
019d75a5list project pipelines
Lists the most recent CI/CD pipelines for a project to check status.
019d75a5list visible groups
Lists all GitLab groups the user has access to.
019d75a5list visible projects
Lists all GitLab projects the user has access to.
019d75a5search gitlab global
Runs a comprehensive search across all projects, issues, and users in GitLab.
019d75a5verify api connection
Checks if the connection between the AI client and GitLab is active and authorized.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with GitLab, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
This server connects your entire development stack to your AI client. It lets your agent manage the full DevSecOps lifecycle—from opening issues to deploying code—all through natural conversation. You can check project metadata, track issues, monitor pipelines, and read file contents across your whole GitLab instance.
To start, your agent first runs verify_api_connection to confirm the link to GitLab is active and authorized. You can check your own profile details by calling get_my_gitlab_profile, which retrieves the identity and profile details of the user logged into GitLab.
You can see what projects and groups are available by running list_visible_groups or list_visible_projects, and you can find out the specific configuration metadata for any project using get_project_details. When you need to search across everything, search_gitlab_global runs a comprehensive search pulling results from projects, issues, and users across your entire GitLab setup.
For managing project tasks, you can list all open or closed issues for a project with list_project_issues, or open a new issue using create_project_issue. You can check all open or merged merge requests for a project with list_merge_requests. You can also list all forks associated with a project by calling list_project_forks.
To monitor deployments, list_project_pipelines lists the most recent CI/CD pipelines for a project, letting you check build and deployment status. You can read the actual contents of any file in a repository using get_repository_file, which reads the text content of a specified file. Finally, you can find everything you need by running search_gitlab_global.
How GitLab MCP Works
- 1 Subscribe to the GitLab server via the Vinkius Marketplace and provide your GitLab Base URL and Personal Access Token.
- 2 Your AI client uses the MCP to call a specific tool, like
list_project_pipelines. - 3 The server executes the API call against GitLab and returns the structured data (e.g., pipeline status, issue list) directly to your AI client.
The bottom line is, your AI client talks to GitLab, and the server translates that conversation into actionable data.
Who Is GitLab MCP For?
The DevSecOps engineer who needs to audit a complex deployment pipeline without logging into three different dashboards. The project manager who needs a real-time overview of project health and open blockers. Or the developer who wants to check a merge request status before switching context from their IDE.
Automates the retrieval of file contents and project metadata for auditing, ensuring compliance and tracking deployment health.
Gets a real-time overview of project activity—like pipeline status or open issues—using simple AI commands instead of manual dashboard navigation.
Quickly checks the status of a merge request or lists open issues without having to manually click through the GitLab UI.
What Changes When You Connect
- Check build health instantly. Instead of clicking into a project dashboard to check the CI/CD status, calling
list_project_pipelinesgives you the latest pipeline status immediately. - Audit code on demand. Need to see what was in
README.mdfrom six months ago? Useget_repository_fileto read the content directly, bypassing file tree navigation. - Centralize project knowledge. Use
search_gitlab_globalto find a specific issue or project across the entire instance, instead of navigating through group hierarchies. - Streamline issue tracking. Instead of manually creating a ticket in the UI, use
create_project_issueto open a new issue directly from your chat prompt. - Track development flow. Quickly list all open merge requests with
list_merge_requeststo understand which code branches are currently under review. - Verify context. Use
get_my_gitlab_profileto confirm your user permissions or check account context before running critical commands.
Real-World Use Cases
Finding the Status of a Stalled Feature
A developer needs to know why Feature X hasn't been merged. They ask their agent to check the status. The agent calls list_project_pipelines (to see if the last build failed) and then list_merge_requests (to see if the MR is stuck). The developer gets the full picture without leaving their terminal.
Onboarding a New Team Member
A project manager needs to hand off project context to a new hire. They ask the agent to list all visible projects (list_visible_projects) and then retrieve the main project metadata (get_project_details). The agent compiles a digestible report, saving hours of manual documentation gathering.
Compliance Audit of Codebase
A security engineer needs to verify the version of a specific dependency. They prompt the agent to read a file (get_repository_file) in the core repository. The agent retrieves the file content, allowing the engineer to verify the version number instantly for auditing purposes.
Tracking Down a Specific Bug Report
A tech lead remembers a specific bug report but can't find the issue number. They ask the agent to search globally using search_gitlab_global with keywords like 'auth bug' and the project name. The agent returns the link and details of the matching issue.
The Tradeoffs
Manually switching dashboards
A developer gets the issue status from the Issues tab, then clicks over to the Pipelines tab, and finally has to copy the MR ID to check the code in the Code tab. This takes 5-10 minutes of context switching.
→
Instead, ask your agent to use list_project_issues, list_project_pipelines, and list_merge_requests sequentially. The agent runs all three tools and synthesizes a single, comprehensive status report in the chat.
Assuming full access
A new user assumes they can see all projects and try to run a global search before verifying their permissions. The search fails, leaving the user unsure if the failure was due to permissions or a bad query.
→
Start by calling get_my_gitlab_profile to confirm your access level. Then, use list_visible_groups and list_visible_projects to scope your search correctly before running search_gitlab_global.
Ignoring the pipeline state
A developer sees a merge request is ready, but doesn't check the build status. They assume the code passed CI/CD, leading to potential integration failures later.
→
Before merging, ask the agent to run list_project_pipelines on the target project. This confirms the most recent build passed successfully, ensuring the code is deployable.
When It Fits, When It Doesn't
Use this if your primary job involves correlating data points across the full development lifecycle—i.e., you need to know if an Issue is linked to a Merge Request, if that MR is associated with a passing Pipeline, and what files were changed. You must be dealing with multi-stage, interconnected project data. Don't use this if you just need to check a single piece of data (e.g., 'What is the status of issue #123?'). For that, a simpler, single-purpose issue tracker or ticketing system is sufficient. If you only need to read file contents, the get_repository_file tool handles that job fine, but this server gives you the whole picture.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by GitLab. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 16 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Tracking project status shouldn't require 10 clicks.
Today, checking a project's status means opening the main dashboard, navigating to the Issues tab to check blockers, then clicking to the Merge Requests section to see code status. You then have to switch tabs again to the CI/CD section just to see if the latest build passed. It's a mess of context switching and manual data correlation.
With this MCP server, you just ask: 'What's the status of the auth fix MR?' The agent runs `list_merge_requests` and `list_project_pipelines` simultaneously, giving you a single, definitive answer right in your chat window.
GitLab MCP Server: Get the full project picture from your chat.
The biggest time sink goes away: manually cross-referencing a bug report's ID (from the Issues tab) with the correct branch (from the MR tab) and then running a manual pipeline check. You stop hopping between tabs.
Now, you can ask complex questions—like 'Show me all open issues in the 'Infra' group that haven't been linked to a pipeline in the last 24 hours.' The system handles the lookup; you just get the answer.
Common Questions About GitLab MCP
How do I get a Personal Access Token (PAT) for GitLab? +
Log in to GitLab, go to User Settings > Access Tokens, and you can generate a new token with the 'api' scope there.
Does this support self-hosted GitLab instances? +
Yes! Simply provide your instance's root URL (e.g., https://gitlab.my-company.com) in the 'GitLab Base URL' credential field.
What is a 'Project ID' in GitLab? +
A Project ID is a unique numerical identifier for your project. You can also use the URL-encoded path (e.g., 'group%2Fproject') in most tools.
Can I see pipeline failures via the agent? +
Yes! Use the 'list_project_pipelines' tool to retrieve the status of all recent pipelines, allowing you to quickly identify failed builds.
How do I use the `list_visible_projects` tool to find a project? +
The list_visible_projects tool returns a list of all projects the authenticated user can access. You can then use the project name or ID to feed into other tools, like get_project_details, for deeper analysis.
What happens if I try to read a file with `get_repository_file` but the file doesn't exist? +
If the file doesn't exist, the tool returns a specific error message detailing the missing path. This means your agent client can handle the failure gracefully and prompt you to check the file path.
Does the `search_gitlab_global` tool search across all user types or just code? +
The global search tool indexes projects, issues, and user metadata across your entire GitLab instance. It finds artifacts by keyword, not just code contents.
How does `create_project_issue` handle required fields for a new issue? +
The tool requires specific fields like the project ID, title, and description to create an issue. If any mandatory data is missing, the function call fails, preventing incomplete records.
Multi-server workflows that include GitLab MCP
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Merge request velocity measured, pipeline success rates tracked, cycle time calculated, team metrics published , build your DORA dashboard without a BI tool
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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