GitLab MCP Server: Governed AI Access

GitLab's MCP server includes 28 different actions available to any connected model or AI agent. When registered with Barndoor, you can ensure centralized governance, visibility, and control across every AI agent your team uses.

Tools 28
Capabilities Create, Read, Update
Category Developer & Version Control
Type Barndoor Hosted

What can AI agents do with the GitLab MCP server?

Tools Available

• createIssue
  create
  Create a new issue in a GitLab project.

• listProjects
  read
  Get a list of all visible projects across GitLab for the authenticated user.

• getMergeRequest
  read
  Get detailed information about a specific merge request in a GitLab project.

• createMergeRequest
  create
  Create a new merge request in a GitLab project.

• mergeMergeRequest
  update
  Accept and merge a merge request.

• editIssue
  update
  Update an existing issue. Use state_event to close or reopen.

See full list →

Use cases for GitLab

• Merge Request Workflow
  "Create and review MRs", "Approve and merge changes", "Track MR pipelines"

• Issue Management
  "Create and edit issues", "Comment on issues", "Filter by labels"

• Repository Operations
  "Manage branches", "Browse repository files", "Search projects"

• CI CD Monitoring
  "Inspect pipeline jobs", "View job logs", "Track milestones"

What are the risks of using the GitLab MCP without an AI gateway?

• Uncontrolled reads — AI agents can pull data out of GitLab with no visibility into what was accessed.
• Ungoverned writes — agents can create or modify records in GitLab with no approval step.
• Destructive actions — agents can delete or overwrite GitLab data with no approval gate or audit trail.

Why connect GitLab with the Barndoor AI gateway?

Barndoor MCP Governance is the gateway between your AI agents and the tools they use.

• Centralized MCP management — One place to manage and control every MCP server across the organization so your team has an approved catalog of MCP servers that employees and AI agents connect through.
• Universal connection — One universal URL works across every AI provider your team uses.
• Fine-grained access controls — Set access policies for how AI is connecting with GitLab based on human identities, agent profiles, tool-access, context, and data fields.
• Protect sensitive data — Keeps sensitive data from reaching a model or AI agent with PII detection, masking, tokenization, redaction, and more.
• Observability — Real-time reporting and dashboards that give you visibility into what AI is doing with GitLab, how policies are being enforced, and who (human or agent) is doing what.
• Enterprise-grade security — Stay compliant with audit trails and logging.

Getting started with GitLab in Barndoor

1. Connect the GitLab MCP server once
2. Define your policies
3. Go live across every AI client

See the full setup guide →

Frequently asked questions

• What is MCP?
  MCP (Model Context Protocol) is the open standard that lets AI models and agents connect to external tools and data sources through a common interface.

• Is Barndoor secure?
  Yes. Barndoor is SOC 2 Type II compliant.

• How are GitLab schema changes handled?
  Barndoor tracks tool and schema changes on GitLab.

• Do you integrate with my identity provider?
  Barndoor authenticates admins and policy managers through your OIDC or SAML 2.0 identity provider.

• Do users have to enter tokens manually?
  No. Barndoor brokers the OAuth connection to GitLab centrally.

• How does Barndoor integrate with AI agent identities?
  Barndoor gives each AI agent its own governed identity called an AgentProfile.

• Can I deploy custom-built MCP servers?
  Yes. Barndoor supports customer-built MCPs.

• Can I set and audit tool-level access across teams?
  Yes. Barndoor's access control is fine-grained.

• How can I get started with GitLab and Barndoor?
  Connect GitLab once, define your access policies, and go live across every AI client your team uses.