GitLab DevOps MCP Server

A Model Context Protocol (MCP) server that lets Claude Code (or any MCP client) operate GitLab end-to-end. ~50 typed tools covering the full DevOps lifecycle.

What it does

Category	Tools
Repo & branch	clone, batch commit, branch creation, file ops
Pipelines	trigger, monitor, retry, cancel
CI generation	generate .gitlab-ci.yml for common stacks (Node, Python, Go, generic)
Security scans	SAST, DAST, secret detection, dependency, container scanning
Pipeline failure analysis	log fetching, root-cause classification, suggested fix
Runners	register local runners, pause/unpause, retag
Access tokens	full lifecycle for personal / project / group tokens
Merge requests	create, list, merge, comment

Why this exists

GitLab automation is normally split across glab, the GitLab API, ad-hoc Python scripts, and CI YAML. This MCP server exposes everything as a single set of typed tools that an AI agent (or human via chat) can call.

Install

pip install -r requirements.txt
cp .env.example .env
# Edit .env — set GITLAB_TOKEN

Add to your MCP client config:

{
  "mcpServers": {
    "gitlab-devops": {
      "command": "python3",
      "args": ["/absolute/path/to/server.py"]
    }
  }
}

Usage examples

In any MCP client:

• "Generate a Terraform pipeline for project X"
• "Why did pipeline 12345 fail?" → reads logs, classifies, suggests fix
• "Run a SAST scan on the latest commit"
• "List all my open MRs across all projects"
• "Revoke the leaked access token in the my-org/my-repo group"

Architecture

Modular — each capability area lives in its own file under tools/:

tools/
├── gitlab_repo.py        # repos, branches, files
├── gitlab_pipeline.py    # CI/CD lifecycle
├── ci_generator.py       # YAML scaffolding
├── gitlab_security.py    # SAST / DAST / scans
├── gitlab_runner.py      # runner registration
├── error_analyzer.py     # log → root cause → fix
└── gitlab_tokens.py      # access token lifecycle

License

MIT — see LICENSE.

Support

See SUPPORT.md for community + commercial support.