GitLab-MCP-Server

Name: GitLab-MCP-Server
Author: MCP-Mirror

@MCP-Mirror

リポジトリ

GitLab-MCP-Server について

Mirror of

#gitlab #mcp-server #ai-assistant

基本情報

カテゴリ

バージョン管理

ライセンス

MIT license

ランタイム

python

トランスポート

stdio

公開者

MCP-Mirror

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "owayo_gitlab-mcp-server": {
      "command": "uv",
      "args": [
        "sync"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is GitLab-MCP-Server?

GitLab-MCP-Server is a Model Context Protocol (MCP) server that connects AI assistants to GitLab projects. It retrieves pipeline failure logs, unresolved merge request review comments, and local changes against the MR base commit, enabling the assistant to act on that information.

How to use GitLab-MCP-Server?

Install with uv sync after cloning the repository. Obtain a GitLab personal access token with the read_api scope. Configure the server by setting environment variables (GITLAB_URL, GITLAB_PROJECT_NAME, GITLAB_API_KEY, GIT_REPO_PATH) in your client's MCP configuration (Claude Desktop or Cursor). The tools are then available via MCP function calls: get_pipeline_failed_jobs, get_review_comments, and get_review_changes.

Key features of GitLab-MCP-Server

get_pipeline_failed_jobs: fetches console output of failed pipeline jobs
get_review_comments: retrieves unresolved, file‑attached MR comments
get_review_changes: gets diff from MR base commit to local repository state
Uses GitLab API with a read‑only token
Works with Claude for Desktop and Cursor

Use cases of GitLab-MCP-Server

Diagnose and fix CI pipeline failures by examining job logs
Address unresolved review comments on a merge request
Review the full set of changes (including uncommitted local modifications) against the MR base

FAQ from GitLab-MCP-Server

What does GitLab-MCP-Server do that regular GitLab API access doesn't?

It exposes GitLab data through MCP tools, letting an AI assistant directly retrieve and act on pipeline failures, MR comments, and changes without manual API calls.