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poly-mcp

GitLab MCP Server

by poly-mcp
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Python
Remote

GitLab MCP Server

Python 3.8+ License MIT MCP Compatible

An MCP (Model Context Protocol) server for integrating GitLab with AI assistants like Cursor, ChatGPT, and any polymcp-compatible client. Manage merge requests, analyze CI/CD pipelines, create ADR documents, and more.

What it does

This project exposes GitLab APIs through the MCP protocol, allowing AI assistants to:

  • List and manage merge requests

  • Analyze failed pipeline jobs with fix suggestions

  • Create ADR (Architecture Decision Records) documents in markdown

  • View CI/CD job logs

  • Trigger pipelines and retry failed jobs

  • Deploy to AWS, Azure, and GCP

Requirements

  • Python 3.8 or higher

  • PolyMCP (for AI agent integration)

  • FastAPI and uvicorn (for HTTP server)

Installation

git clone https://github.com/poly-mcp/Gitlab-MCP-Server.git cd Gitlab-MCP-Server pip install -r requirements.txt

Contents of requirements.txt:

fastapi>=0.104.0 uvicorn>=0.24.0 aiohttp>=3.9.0 pyyaml>=6.0 docstring-parser>=0.15 python-dotenv>=1.0.0 pydantic>=2.0.0 pip install polymcp==1.2.4

Configuration

Create a .env file in the project root:

# For use with real GitLab GITLAB_BASE_URL=https://gitlab.com/api/v4 GITLAB_TOKEN=glpat-xxxxxxxxxxxx GITLAB_PROJECT_ID=12345678 # Optional - security settings SAFE_MODE=true DRY_RUN=false

Usage with PolyMCP

This server is fully compatible with the polymcp library. Here is how to use it:

1. Start the server

# Production mode (requires token) python gitlab_mcp_server.py --http --port 8000

2. Connect with polymcp

Create a file gitlab_chat.py:

#!/usr/bin/env python3 """GitLab MCP Chat with PolyMCP""" import asyncio from polymcp.polyagent import UnifiedPolyAgent, OllamaProvider async def main(): # Configure the LLM provider (you can use OpenAI, Anthropic, Ollama, etc.) llm = OllamaProvider(model="gpt-oss:120b-cloud", temperature=0.1) # Point to the GitLab MCP server mcp_servers = ["http://localhost:8000/mcp"] agent = UnifiedPolyAgent( llm_provider=llm, mcp_servers=mcp_servers, verbose=True ) async with agent: print("\nGitLab MCP Server connected!\n") print("Available commands:") print("- 'show me open merge requests'") print("- 'analyze failed jobs'") print("- 'create an ADR for cloud migration'") print("- 'exit' to quit\n") while True: user_input = input("\nYou: ") if user_input.lower() in ['exit', 'quit']: print("Session ended.") break result = await agent.run_async(user_input, max_steps=5) print(f"\nGitLab Assistant: {result}") if __name__ == "__main__": asyncio.run(main())

3. Run it

python gitlab_chat.py

Example session:

GitLab MCP Server connected! You: show me open merge requests in project mygroup/myproject GitLab Assistant: I found 3 open merge requests: 1. MR !42 - "Fix authentication bug" Author: john_doe Branch: bugfix/auth -> main 2. MR !43 - "Add caching layer" Author: jane_smith Branch: feature/cache -> main 3. MR !44 - "Update dependencies" Author: bob_wilson Branch: chore/deps -> main You: analyze why the pipeline is failing GitLab Assistant: I analyzed pipeline #12345. There are 2 failed jobs: 1. test:unit (stage: test) Error: Snapshot test mismatch Suggestion: Run 'npm test -- -u' to update snapshots 2. security:sonar (stage: security) Error: Code coverage below threshold (67% < 80%) Suggestion: Add tests for uncovered functions You: exit Session ended.

Usage with Cursor

Method 1 - Direct import

Copy cursor_tools.py to your project and use it directly:

from cursor_tools import * # List merge requests mrs = list_open_merge_requests("mygroup/myproject") # Analyze pipeline analysis = analyze_pipeline_failures("mygroup/myproject") # Create ADR adr = create_architecture_decision( title="Kubernetes Adoption", context="We need to scale horizontally", decision="We will migrate to Kubernetes on GKE", consequences="Higher operational complexity but better scalability" )

Method 2 - MCP Configuration

Add to .cursor/mcp_config.json:

{ "mcpServers": { "gitlab": { "command": "python", "args": ["gitlab_mcp_server.py", "--mode", "stdio"] } } }

Usage with ChatGPT

  1. Start the server and expose it publicly (with ngrok or similar):

python gitlab_mcp_server.py --http --port 8000 ngrok http 8000

  1. Create a Custom GPT with Actions pointing to the ngrok URL

  2. Or use Code Interpreter by uploading gitlab_assistant.py

Safety Features

The server includes built-in protections:

Feature

Default

What it does

Safe Mode

ON

Blocks write operations until you're ready

Dry Run

OFF

Test operations without executing them

Project Allowlist

* (all allowed)

Use * for all, empty to block all, or list specific projects

Rate Limiting

60/min

Prevents API abuse

💡 Start with SAFE_MODE=true to explore safely, then disable when needed.

Available Tools

Merge Request Management

Tool

Description

list_merge_requests

List merge requests with filters (state, author, assignee)

get_merge_request_details

Get MR details including changes and discussions

create_merge_request

Create a new merge request

approve_merge_request

Approve a merge request

merge_merge_request

Merge a merge request into target branch

rebase_merge_request

Rebase a merge request onto target branch

Code Search

Tool

Description

search_code

Search for code across project files

Pipeline & CI/CD

Tool

Description

list_pipeline_jobs

List all jobs in a pipeline with status

get_job_log

Get the log output of a specific job

analyze_failed_jobs

Analyze failures and suggest fixes

trigger_pipeline

Trigger a new pipeline run

retry_pipeline

Retry all failed jobs in a pipeline

cancel_pipeline

Cancel a running pipeline

retry_failed_job

Retry a specific failed job

ADR (Architecture Decision Records)

Tool

Description

create_adr_document

Create an ADR document in Markdown format

commit_adr_to_gitlab

Commit ADR to repository with optional MR

Cloud Deployment

Tool

Description

deploy_to_cloud

Deploy to AWS, Azure, or GCP via pipeline

Security

To use the server safely with Cursor or other AI assistants:

  1. Create a GitLab token with minimal permissions (only read_api and read_repository)

  2. Enable SAFE_MODE=true in the .env file to disable destructive operations

  3. Use DRY_RUN=true to simulate operations without executing them

  4. Limit accessible projects by configuring ALLOWED_PROJECTS

The server tracks all operations and provides usage statistics.

Project Structure

Gitlab-MCP-Server/ ├── gitlab_mcp_server.py # Main server ├── cursor_tools.py # Wrapper for Cursor ├── gitlab_chat.py # Client for PolyMCP ├── gitlab_assistant.py # Client for ChatGPT ├── .env.example # Configuration template ├── requirements.txt # Dependencies └── README.md

Troubleshooting

Error

Solution

GITLAB_TOKEN is required

Create .env file with your token

Operation blocked by safe mode

Set SAFE_MODE=false in .env

Access denied to project

Check token permissions or ALLOWED_PROJECTS

Request timed out

Increase MAX_RETRIES in .env

Contributing

Contributions are welcome. Open an issue to discuss significant changes before proceeding with a pull request.

License

MIT License - see LICENSE file for details.

Useful Links

This server cannot be installed

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security - not tested
A
license - permissive license
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quality - not tested

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