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MCP Server
Barndoor Hosted
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.
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.
Use cases for GitLab
Merge Request Workflow
Issue Management
Repository Operations
CI CD Monitoring
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.
| At a glance | Available? |
|---|---|
| Fine-grained access controls policies per agent, team, role, user, MCP server and tool call | Yes |
| Approval required before write/destructive actions | Yes (configurable per role) |
| Full audit log (reads and writes) | Yes |
| Sensitive data detection before it reaches a model or agent | Yes |
| Instant access revocation | Yes |
| SOC 2 Type II compliant | Yes |
- 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.
Works with every AI client
Getting started with GitLab in Barndoor
- Connect the GitLab MCP server once
- Define your policies
- Go live across every AI client
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, instead of a custom integration for every tool. GitLab is an MCP server that exposes a defined set of tools an AI agent can call. Barndoor sits at that connection point, applying access policies and audit logging to every tool call regardless of which AI client is making it.
Is Barndoor secure?
Yes. Barndoor is SOC 2 Type II compliant. Barndoor enforces fine-grained access control, requires approval before destructive actions, protects sensitive data with data loss prevention, and logs every action for audit.
How are GitLab schema changes handled?
Barndoor tracks tool and schema changes on GitLab. New or changed tools inherit deny-by-default access until an admin reviews and approves them, keeping runtime enforcement current without manual reconfiguration. Every schema change is captured in the audit trail alongside who approved it.
Do you integrate with my identity provider?
Barndoor authenticates admins and policy managers through your OIDC or SAML 2.0 identity provider. Signing into Claude, Cursor, or ChatGPT still happens directly with those providers. Barndoor's integration point is the GitLab connection where access policies apply to what an agent can do once it's connected.
Do users have to enter tokens manually?
No. Barndoor brokers the OAuth connection to GitLab centrally, so users and agents never handle or store a standing token themselves. Access is granted and revoked through policy instead of shared credentials.
How does Barndoor integrate with AI agent identities?
Barndoor gives each AI agent its own governed identity called an AgentProfile, separate from the human who configured or uses it. AgentProfile lets policies and audit logs attribute a given action to the specific agent, not a shared service token, so you can set different access rules per agent and revoke one agent's access without affecting others.
Can I deploy custom-built MCP servers?
Yes. Barndoor supports customer-built MCPs, so internal tools and systems your team builds get the same policy enforcement and audit trail as Barndoor MCPs and official MCPs.
Can I set and audit tool-level access across teams?
Yes. Barndoor's access control is fine-grained, down to the agent, team, group, user, MCP server, the specific tool call, and the data type involved. Every call is logged with a timestamp, the user or agent calling it, the client it came from, and the result of the policy applied, so you can see exactly who or what did what, when, and whether it was allowed, across any team or role.
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. Setup takes three steps: connect the server, define policies by role or agent, and roll out to Claude, Cursor, ChatGPT, and any other MCP-compatible client. Request a demo at barndoor.ai/get-a-demo to learn more.
Connect GitLab to your AI agents with Barndoor.
Join AI-forward enterprises using Barndoor MCP Governance to manage and secure GitLab integrations with AI and AI agents.