GitLab MCP Server

@MCP-Mirror

リポジトリ

基本情報

カテゴリ

バージョン管理

ライセンス

MIT license

トランスポート

stdio

作者

MCP-Mirror

GitLab MCP Server について

Mirror of

#gitlab #mcp-server #ai-assistant

GitLab MCP Server の設定

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"
      ]
    }
  }
}

GitLab MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

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

よくある質問

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.

What are the runtime dependencies?

Python with `uv`, a local Git repository, a network connection to the GitLab instance, and a GitLab access token with `read_api` scope.

Where does the data come from?

Data is fetched live from the GitLab API and from the local Git repository on the machine running the server. No external storage is used.

Does it support authentication?

Yes, via a GitLab personal access token set as the `GITLAB_API_KEY` environment variable. The token must have the `read_api` scope.

How is the server started?

It runs as an MCP subprocess via `uv run main.py` from its directory, configured as a command in the client’s `mcpServers` block.

「バージョン管理」の他のコンテンツ

AIO-MCP Server

athapong

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