GitLab-MCP-Server

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

@MCP-Mirror

代码仓库

关于 GitLab-MCP-Server

Mirror of

#gitlab #mcp-server #ai-assistant

基本信息

分类

版本控制

许可证

MIT license

运行时

python

传输方式

stdio

发布者

MCP-Mirror

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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.

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.

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