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GitLab PR Analysis MCP Server: Automates Code Reviews, Secures Merges - MCP Implementation

GitLab PR Analysis MCP Server: Automates Code Reviews, Secures Merges

GitLab PR Analysis MCP Server automates code reviews, ensures quality, and fast-tracks secure merges, empowering dev teams to deliver faster with confidence." )

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About GitLab PR Analysis MCP Server

What is GitLab PR Analysis MCP Server: Automates Code Reviews, Secures Merges?

This tool bridges GitLab merge request workflows with Confluence documentation via an MCP server. It automates the extraction, analysis, and storage of code review data, ensuring seamless tracking of changes and compliance with documentation standards. By integrating API-driven code audits with centralized knowledge bases, it reduces manual overhead while maintaining rigorous quality control during merge processes.

How to Use GitLab PR Analysis MCP Server: Automates Code Reviews, Secures Merges?

Setup Steps

  1. Clone the repository and activate a Python virtual environment
  2. Configure credentials in .env for GitLab and optional Confluence access
  3. Launch the server via command-line or Claude Desktop integration

Interactive Commands

  • Fetch MR details: Can you fetch details for merge request #1 from project "my-project"?
  • Analyze code changes: Can you analyze code changes in merge request #1 from project "my-project"?
  • Store reports: Can you store a summary of merge request #1 from project "my-project" in Confluence?

GitLab PR Analysis MCP Server Features

Key Features of GitLab PR Analysis MCP Server: Automates Code Reviews, Secures Merges?

Code Audit Automation

Automates statistical analysis of added/removed lines, modified files, and language-specific changes

Confluence Integration

Stores analysis summaries directly into pre-configured Confluence spaces with versioned page updates

Comprehensive Logging

Generates timestamped logs for API failures, authentication issues, and integration bottlenecks

Granular Control

Supports both single MR analysis and bulk processing across multiple GitLab projects

Use Cases of GitLab PR Analysis MCP Server: Automates Code Reviews, Secures Merges?

  • Automated Documentation Synchronization – Keep Confluence pages updated with real-time code change summaries
  • Security Compliance Checks – Flag sensitive code patterns (e.g., hardcoded credentials) during analysis
  • Team Collaboration Enhancement – Provide auditable records for code reviews in shared knowledge bases
  • CI/CD Pipeline Integration – Embed analysis results into deployment workflows for quality gates

GitLab PR Analysis MCP Server FAQ

FAQ from GitLab PR Analysis MCP Server: Automates Code Reviews, Secures Merges?

Does this work with self-hosted GitLab instances?

Yes, configure GITLAB_URL with your instance's base address in the environment file

What happens if Confluence access is denied?

Analysis proceeds but logging highlights permission failures; results remain available locally

Can I customize report content?

Output structure is fixed but Confluence page templates can be modified externally

How are API rate limits handled?

Exponential backoff and retry mechanisms built into GitLab API client implementation

Content

GitLab PR Analysis MCP Server

This project provides an MCP (Model Control Protocol) server that integrates GitLab merge request analysis with Confluence documentation. It allows you to fetch merge request details, analyze code changes, and store the results in Confluence pages.

Features

  • Fetch merge request details from GitLab
  • Analyze code changes in merge requests
  • Generate detailed reports including:
    • Basic merge request information
    • Code change statistics
    • File type analysis
    • Detailed file changes
  • Store analysis results in Confluence
  • Comprehensive logging for debugging

Prerequisites

  • Python 3.8 or higher
  • GitLab account with API access
  • Confluence account (optional, for storing analysis results)
  • Access to the required GitLab project(s)

Installation

  1. Clone the repository:
git https://github.com/CodeByWaqas/MRConfluenceLinker-mcp-server.git
cd MRConfluenceLinker-mcp-server
  1. Create and activate a virtual environment:
python -m venv .venv
source .venv/bin/activate  # On Windows, use: .venv\Scripts\activate
  1. Install dependencies:
pip install -r requirements.txt

or

uv add "mcp[cli]" python-gitlab python-dotenv atlassian-python-api requests

Configuration

  1. Copy the example environment file:
cp .env.example .env
  1. Edit the .env file with your credentials:
GITLAB_URL=https://gitlab.com
GITLAB_TOKEN=your_gitlab_token
GITLAB_PROJECT_ID=your_project_id

# Optional Confluence integration
CONFLUENCE_URL=your_confluence_url
CONFLUENCE_USERNAME=your_username
CONFLUENCE_TOKEN=your_confluence_token
CONFLUENCE_SPACE=your_space_key

Obtaining Credentials

  • GitLab Token : Generate a personal access token in GitLab with api scope
  • Confluence Token : Generate an API token in your Atlassian account settings

Usage

  1. Start the MCP server:
python src/MRConfluenceLinker-mcp-server/server.py

or

Setup with Claude Desktop

# claude_desktop_config.json
# Can find location through:
# Claude -> Settings -> Developer -> Edit Config
{
  "mcpServers": {
      "MRConfluenceLinker-mcp-server": {
          "command": "uv",
          "args": [
              "--directory",
              "/<Absolute-path-to-folder>/MRConfluenceLinker-mcp-server/src/MRConfluenceLinker-mcp-server",
              "run",
              "server.py"
          ]
      }
  }
}

2. The server will listen for commands through stdin/stdout. You can interact with it using prompts like:

Can you fetch details for merge request #1 from project "my-project"? Can you analyze code changes in merge request #1 from project "my-project"? Can you store a summary of merge request #1 from project "my-project" in Confluence?

## Available Tools

The server provides the following tools:

1. `fetch_mr_details`: Fetches details of a specific merge request or all merge requests
   - Parameters:
     - `project_id`: The GitLab project ID
     - `mr_id` (optional): Specific merge request ID

2. `analyze_code_changes`: Analyzes code changes in a merge request
   - Parameters:
     - `project_id`: The GitLab project ID
     - `mr_id`: The merge request ID to analyze

3. `store_in_confluence`: Stores analysis results in Confluence
   - Parameters:
     - `project_id`: The GitLab project ID
     - `mr_id` (optional): Specific merge request ID
     - `analysis` (optional): Analysis results to store

## Logging

The server generates detailed logs in `mcp_server.log` and outputs to stderr. This helps in debugging issues with:
- GitLab API access
- Confluence integration
- Code analysis
- Page creation and updates

## Error Handling

The server includes comprehensive error handling for:
- Missing environment variables
- API authentication issues
- Network connectivity problems
- Invalid project or merge request IDs
- Confluence permission issues

## Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

## License

This project is licensed under the MIT License - see the LICENSE file for details.

## Support

For support, please [create an issue](https://github.com/CodeByWaqas/MRConfluenceLinker-mcp-server/issues) or contact the maintainers.

## Project Structure

MRConfluenceLinker-mcp-server/ ├── src/ # Source code directory │ └── MRConfluenceLinker-mcp-server/ # Main server package │ ├── resources/ # Resource modules │ │ ├── init.py │ │ ├── client.py # Client implementation / GitLab PR integration │ ├── server.py # Main server implementation │ └── mcp_server.log # Server logs ├── pycache / # Python cache files ├── .git/ # Git repository ├── .gitignore # Git ignore rules ├── CONTRIBUTING.md # Contributing guidelines ├── LICENSE # Project license ├── README.md # Project documentation ├── pyproject.toml # Python project configuration ├── requirements.txt # Project dependencies └── uv.lock # Dependency lock file

### Key Components

- **Source Code**: Located in the `src/MRConfluenceLinker-mcp-server/` directory
  - `server.py`: Main MCP server implementation
  - `resources/client.py`: Client-side implementation contains GitLab PR integration

- **Configuration Files**:
  - `requirements.txt`: Python package dependencies
  - `pyproject.toml`: Project metadata and build configuration
  - `uv.lock`: Locked dependency versions
  - `.env.example`: Environment variables template

- **Documentation**:
  - `README.md`: Project overview and setup instructions
  - `CONTRIBUTING.md`: Contribution guidelines
  - `LICENSE`: Project license

- **Development**:
  - `__pycache__/`: Python cache files
  - `mcp_server.log`: Server logs for debugging

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