What specific GitLab functions can AI assistants perform with this tool?

AI assistants can perform a wide range of tasks including AI-assisted code review, issue analysis, pipeline failure diagnosis, interactive creation of issues/MRs/releases/projects, managing projects, groups, users, and much more, covering all major GitLab domains.

What is the GitLab MCP Server?

The GitLab MCP Server is a Model Context Protocol (MCP) server that exposes over 1000 GitLab REST and GraphQL API operations as tools, resources, and prompts for AI assistants, enabling powerful natural language interaction with GitLab.

How does it help AI assistants interact with GitLab?

It translates natural language prompts into precise GitLab API calls, allowing AI assistants to perform tasks like listing projects, reviewing code, creating issues, or diagnosing pipelines without needing to know API endpoints, project IDs, or JSON syntax.

Is the GitLab MCP Server compatible with self-hosted GitLab and various AI clients?

Yes, it fully supports self-hosted GitLab instances, including those with self-signed TLS certificates. It's compatible with popular MCP clients like VS Code (GitHub Copilot), Claude Desktop, Cursor, JetBrains IDEs, Zed, and Kiro.

What are 'meta-tools' and 'sampling tools'?

'Meta-tools' are domain-grouped dispatchers (42-57 available) that optimize interactions and reduce token overhead for LLMs. 'Sampling tools' (11 available) provide advanced AI-assisted analysis capabilities like code review, issue analysis, and pipeline failure diagnosis.

GitLab MCP Server: AI Tools for Natural Language GitLab API

The GitLab tool acts as a comprehensive Model Context Protocol (MCP) server, transforming GitLab's extensive REST and GraphQL API operations into accessible tools, resources, and prompts specifically designed for AI assistants. It provides over 1000 individual operations, intelligently grouped into 42 meta-tools (57 for enterprise versions) to optimize token usage for Large Language Models. This enables AI to perform a wide range of tasks, from LLM-assisted code reviews and pipeline failure diagnoses to interactive creation wizards for issues, merge requests, and projects. Written in Go, it delivers a single static binary, supporting both stdio and HTTP transports for seamless integration with various AI clients across Windows, Linux, and macOS.

Key Features

01Exposes 1006 GitLab REST & GraphQL API operations as MCP tools

02Offers 42 meta-tools (57 with enterprise features) for optimized LLM interaction

03Includes 11 sampling tools for AI-assisted code review, issue analysis, and pipeline diagnosis

04Provides 4 elicitation tools for interactive creation wizards (issue, MR, release, project)

05Supports stdio and HTTP transports, with cross-platform compatibility and self-hosted GitLab support

060 GitHub stars

Use Cases

01Interact with GitLab projects, issues, and merge requests using natural language via AI assistants

02Automate LLM-assisted code reviews, pipeline failure diagnosis, and security reviews

03Generate release notes, milestone reports, and perform cross-project analytics directly from GitLab data