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GitLab PR Analysis MCP Server

@CodeByWaqas

代码仓库

基本信息

分类

版本控制

许可证

MIT license

传输方式

stdio

作者

CodeByWaqas

关于 GitLab PR Analysis MCP Server

暂无概览

#gitlab#mcp-server#confluence-integration

GitLab PR Analysis MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "MRConfluenceLinker-mcp-server": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        ".venv"
      ]
    }
  }
}

GitLab PR Analysis MCP Server 工具

3

`project_id`: The GitLab project ID

`project_id`: The GitLab project ID

`project_id`: The GitLab project ID

概览

What is GitLab PR Analysis MCP Server?

An MCP server that integrates GitLab merge request analysis with Confluence documentation. It fetches merge request details, analyzes code changes, and stores results in Confluence pages. Designed for developers and teams using GitLab who want automated code review summaries.

How to use GitLab PR Analysis MCP Server?

Install dependencies, create a virtual environment, and copy the .env.example file to .env with your GitLab token, project ID, and optional Confluence credentials. Start the server with python src/MRConfluenceLinker-mcp-server/server.py or configure it as an MCP server in Claude Desktop. The server listens for commands via stdin/stdout.

Key features of GitLab PR Analysis MCP Server?

  • Fetch details of a specific or all merge requests
  • Analyze code changes in a merge request
  • Store analysis results in Confluence
  • Generate reports with code change statistics and file type analysis
  • Comprehensive logging for debugging

Use cases of GitLab PR Analysis MCP Server?

  • Automate merge request summaries for code reviews
  • Document code changes in Confluence for team visibility
  • Track file‑type changes across multiple merge requests
  • Integrate GitLab analysis into an MCP‑aware assistant like Claude Desktop

常见问题

1

What credentials are required?

A GitLab personal access token with `api` scope and a GitLab project ID. For Confluence integration, provide a Confluence URL, username, API token, and space key.

2

What are the runtime dependencies?

Python 3.8 or higher, plus packages: `mcp[cli]`, `python-gitlab`, `python-dotenv`, `atlassian-python-api`, and `requests`.

3

Does the server handle errors?

Yes, it includes handling for missing environment variables, API authentication failures, network issues, invalid project/merge request IDs, and Confluence permission problems.

4

What tools does the server expose?

Three tools: `fetch_mr_details`, `analyze_code_changes`, and `store_in_confluence`. Each accepts a project ID and optional merge request ID.

5

Where are logs stored?

Logs are written to `mcp_server.log` and also output to stderr for debugging GitLab API access, Confluence integration, and code analysis.

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