Usage Examples
These examples show natural language prompts you can use with any AI assistant connected to GitLab MCP Server. The server translates these into GitLab API operations automatically.
List your projects
Section titled “List your projects”Prompt: “Show me my GitLab projects”
The server calls gitlab_project with action: list, returning project names, descriptions, and URLs.
Create an issue
Section titled “Create an issue”Prompt: “Create a bug report in my-group/my-project titled ‘Login page returns 404 after password reset’ with labels bug and priority::high”
The server calls gitlab_issue with action: create, setting the title, description, labels, and project in a single operation.
Manage labels
Section titled “Manage labels”Prompt: “List all labels in the frontend project and create a new label called ‘accessibility’ with color #0052CC”
The server first calls gitlab_label with action: list to show existing labels, then action: create to add the new one.
Track milestones
Section titled “Track milestones”Prompt: “Show me the progress on the Sprint 14 milestone in my-project”
The server calls gitlab_milestone with action: get, returning completion percentage, open/closed issue counts, and due date.
List open merge requests
Section titled “List open merge requests”Prompt: “Show me all open merge requests assigned to me”
The server calls gitlab_merge_request with action: list, filtering by assignee and state.
Analyze MR changes
Section titled “Analyze MR changes”Prompt: “Analyze the code changes in merge request !42 for potential bugs and security issues”
The server uses gitlab_analyze_mr_changes (sampling), which fetches the diff, sends it to the LLM for analysis, and returns a structured review with findings.
Review MR security
Section titled “Review MR security”Prompt: “Do a security review of MR !78 in the backend project”
The server uses gitlab_review_mr_security (sampling), which examines the diff for security vulnerabilities like injection flaws, hardcoded secrets, and authentication issues.
Summarize MR discussion
Section titled “Summarize MR discussion”Prompt: “Summarize the review feedback on MR !42”
The server uses gitlab_summarize_mr_review (sampling), consolidating all review comments and discussions into a concise summary.
Check pipeline status
Section titled “Check pipeline status”Prompt: “What’s the status of the latest pipeline in my-project?”
The server calls gitlab_pipeline with action: list, returning the most recent pipeline’s status, duration, and stages.
Diagnose pipeline failure
Section titled “Diagnose pipeline failure”Prompt: “Why did pipeline #12345 fail?”
The server uses gitlab_analyze_pipeline_failure (sampling), which fetches job logs, identifies the failing step, and provides root cause analysis with suggested fixes.
Review CI configuration
Section titled “Review CI configuration”Prompt: “Check the .gitlab-ci.yml in my-project for best practices”
The server uses gitlab_analyze_ci_configuration (sampling), analyzing the CI config for optimization opportunities, security issues, and best practice violations.
Create a release
Section titled “Create a release”Prompt: “Create release v2.1.0 from tag v2.1.0 in my-project with release notes about the login fix and performance improvements”
The server calls gitlab_release with action: create, associating the release with the tag and setting the description.
Generate release notes
Section titled “Generate release notes”Prompt: “Generate release notes for milestone ‘v2.1’ based on all closed issues and merged MRs”
The server uses gitlab_generate_release_notes (sampling), which collects all issues and merge requests in the milestone and generates categorized release notes (Features, Bug Fixes, Improvements).
Milestone report
Section titled “Milestone report”Prompt: “Give me a progress report for the Q2 milestone”
The server uses gitlab_generate_milestone_report (sampling), providing metrics on completion percentage, velocity, blockers, and projected completion date.
Search Code
Section titled “Search Code”Prompt: “Search for usages of the deprecated authenticateUser function across all my projects”
The server calls gitlab_search with action: code, searching across projects for the specified code pattern.
Find technical debt
Section titled “Find technical debt”Prompt: “Identify technical debt in the backend project”
The server uses gitlab_find_technical_debt (sampling), analyzing issues, code patterns, and project metrics to identify areas of accumulated technical debt.
Manage members
Section titled “Manage members”Prompt: “List all members of the frontend project and their access levels”
The server calls gitlab_member with action: list, returning team members with their roles and permissions.
Deployment analysis
Section titled “Deployment analysis”Prompt: “Analyze the deployment history for the production environment over the last month”
The server uses gitlab_analyze_deployment_history (sampling), examining deployment frequency, success rates, rollback patterns, and DORA-like metrics.