GitLab MCP Server

Connect your AI assistant to GitLab so it can review merge requests, triage pipelines, manage issues, and draft releases — in plain language. One static binary (or a container), 1000+ GitLab tools over the full REST + GraphQL API, working with Claude, Cursor, VS Code, and any MCP client.

You talk to your AI assistant; it does the GitLab work. No project IDs, API endpoints, or JSON to remember.

"Review merge request !15 — is it safe to merge?" · "Why did the last pipeline fail?" · "List open issues assigned to me" · "Generate release notes from v1.0 to v2.0"

🤖 Using an AI assistant? Give it this repository URL and ask it to install the server for your client. Everything a model needs to do it headlessly — the declarative per-client config, claude mcp add one-liners, and defaults — is in llms.txt (no interactive wizard required).

Install in 60 seconds

Pick one. Each path ends with you typing a prompt to your assistant.

One-click install

Each button registers the Docker-based server (auto-pulls the image on first run; you need Docker installed). The Claude Desktop row instead downloads a native .mcpb desktop extension (macOS universal + Windows, no Docker) — open it with Claude Desktop and fill in the settings. Need a token? Create a Personal Access Token with the api scope. Self-managed GitLab? Add a GITLAB_URL env var in your client's MCP config after install.

Claude Code (claude mcp add)

Docker (no install — pulls the image on first run):

claude mcp add gitlab --env GITLAB_TOKEN=glpat-xxxx --transport stdio \
  -- docker run -i --rm -e GITLAB_TOKEN ghcr.io/jmrplens/gitlab-mcp-server:latest --http=false

Or install the native binary first, then register it:

# macOS/Linux (Homebrew)
brew install jmrplens/tap/gitlab-mcp-server
# Linux/macOS (script)
curl -fsSL https://raw.githubusercontent.com/jmrplens/gitlab-mcp-server/main/scripts/install.sh | sh
# Windows (PowerShell)
irm https://raw.githubusercontent.com/jmrplens/gitlab-mcp-server/main/scripts/install.ps1 | iex

claude mcp add gitlab --env GITLAB_TOKEN=glpat-xxxx -- gitlab-mcp-server

Self-managed GitLab? Add --env GITLAB_URL=https://gitlab.example.com (and --env GITLAB_SKIP_TLS_VERIFY=true for self-signed certs).

Guided setup (any client, no flags to remember)

The binary ships a setup wizard that collects your GitLab token and configures your MCP client for you — ideal if you'd rather not edit JSON:

gitlab-mcp-server --setup

It auto-detects VS Code, Claude Desktop, Claude Code, Cursor, and Windsurf and writes the right config. On Windows, double-click the .exe to launch it.

Manual JSON (Claude Desktop, Cursor, VS Code, …)

Native binary (Claude Desktop mcpServers, Cursor, etc.):

{
  "mcpServers": {
    "gitlab": {
      "command": "/path/to/gitlab-mcp-server",
      "env": { "GITLAB_TOKEN": "glpat-xxxxxxxxxxxxxxxxxxxx" }
    }
  }
}

VS Code (.vscode/mcp.json, note servers + type):

{
  "servers": {
    "gitlab": {
      "type": "stdio",
      "command": "/path/to/gitlab-mcp-server",
      "env": { "GITLAB_TOKEN": "glpat-xxxxxxxxxxxxxxxxxxxx" }
    }
  }
}

Docker variant — replace "command"/"args" with:

"command": "docker",
"args": ["run", "-i", "--rm", "-e", "GITLAB_TOKEN", "ghcr.io/jmrplens/gitlab-mcp-server:latest", "--http=false"]

For a shared, long-running HTTP deployment instead of per-user stdio, see HTTP Server Mode.

Then just ask: open your AI client and try "List my GitLab projects." See the Getting Started guide for per-client details and more example prompts.

Related MCP server: GitLab MCP Server

Why this server

• 🗣️ Plain-language GitLab. The AI translates "is MR !15 safe to merge?" into the right API calls. You don't touch endpoints, IDs, or JSON.

• 🧰 The whole platform — 1000+ tools. Broad GitLab REST v4 + GraphQL coverage: projects, branches, tags, releases, merge requests, issues, pipelines, jobs, groups, users, wikis, environments, deployments, packages, container registry, runners, feature flags, CI/CD variables, security, admin, tokens, and more.

• 🪶 Low-token by default. The default dynamic surface exposes just 2 tools (find + execute) while reaching the full catalog — so it fits any client's context window. (Token footprint →)

• ✅ Proven with real models. An automated evaluator runs Anthropic, Google, OpenAI, and Qwen against live GitLab instances: 99.5% aggregate success across thousands of operations. (Results →)

• 🔒 Safe by design. Read-only mode, safe mode (dry-run preview of every mutation), TLS options for self-hosted GitLab, and continuous SonarCloud quality/security gates.

• 🖥️ Runs anywhere. One static binary or container; Windows, Linux & macOS; amd64 & arm64; stdio (desktop) and HTTP (remote).

• 45 MCP resources (read-only data: projects, issues, pipelines, MRs, branches, members, the surface-aware gitlab://tools manifest, and workflow best-practice guides).

• 37 MCP prompts (code review, pipeline status, risk assessment, release notes, standup, analytics, audit, and more).

• 4 elicitation wizards (interactive issue/MR/release/project creation).

• 3 MCP capabilities (completions, progress, elicitation) and 50 SVG tool icons for visual identification in MCP clients.

• Pagination on every list endpoint with full metadata.

Tool surfaces

The server can present GitLab in three shapes, controlled by TOOL_SURFACE. The default needs no configuration.

Tool counts scale with your GitLab edition (GITLAB_TIER); higher tiers expose more actions. See Dynamic Toolset and Meta-Tools Reference for the ranking model, safety guards, and full catalogs. For dynamic runs where resources dominate context, set CAPABILITY_SURFACE=minimal.

Token Footprint

Measured with go run ./cmd/audit_tokens/ -footprint against the current catalog. Totals estimate startup context visible to an MCP client: visible tool schemas plus shared resources and prompts, using the cl100k_base tokenizer (GPT-4/GPT-3.5 encoding). For the full matrix (meta and individual surfaces, all META_PARAM_SCHEMA modes), see Token Footprint Reference.

Default configuration: with TOOL_SURFACE unset or TOOL_SURFACE=dynamic, CAPABILITY_SURFACE=full, META_TOOLS unset, META_PARAM_SCHEMA=opaque, and GITLAB_TIER unset (detected, fallback free), the server uses the dynamic find/execute surface. Use TOOL_SURFACE=meta only when you explicitly want domain meta-tools; use TOOL_SURFACE=individual only when your client can handle the full tool catalog.

Rows use the base Community Edition catalog unless the Tier column says otherwise. GITLAB_TIER controls which actions are available; higher tiers expose more tools and thus more reachable actions.

Compatibility

Tested with: VS Code + GitHub Copilot, Claude Desktop, Claude Code, Cursor, Windsurf, JetBrains IDEs, Zed, Kiro, Cline. See the full Compatibility Matrix.

AI Model Tool-Use Evaluation

The project includes an automated evaluator for model-facing MCP quality. It runs schema-only checks against the tool catalog or executes validated model tool calls through MCP against Docker GitLab CE or licensed Enterprise instances populated with fixtures. It measures whether each model chooses the correct action, sends valid parameters, recovers from actionable GitLab errors, and respects destructive-action safeguards — across Anthropic, Google, OpenAI, and Qwen.

Current published result: Docker CE dynamic 20260627-232303.

The published model-evaluation set covers 596 task attempts and 2220 expected MCP operations. Across the selected reports, models emitted 2265 tool calls over 2265 model requests, with 99.5% aggregate final success. See AI Model Evaluation Results for the detailed current matrix.

Current published result: Docker Enterprise meta 20260527.

The published model-evaluation set covers 92 task attempts and 336 expected MCP operations. Across the selected reports, models emitted 345 tool calls over 350 model requests, with 100.0% aggregate final success. See AI Model Evaluation Results for the detailed current matrix.

Current published result: Docker Enterprise dynamic 20260628-015421.

The published model-evaluation set covers 124 task attempts and 808 expected MCP operations. Across the selected reports, models emitted 817 tool calls over 817 model requests, with 100.0% aggregate final success. See AI Model Evaluation Results for the detailed current matrix.

Documentation

Full documentation is at jmrplens.github.io/gitlab-mcp-server. Use this map for the source-of-truth reference on a specific area:

FAQ

Yes. Set GITLAB_URL to your instance URL. When GITLAB_URL is omitted, stdio mode uses https://gitlab.com. Self-signed TLS certificates are supported via GITLAB_SKIP_TLS_VERIFY=true.

The server runs locally on your machine (stdio mode) or on your own infrastructure (HTTP mode). No data is sent to third parties — all API calls go directly to your GitLab instance. See SECURITY.md for details.

Yes. Set GITLAB_READ_ONLY=true to disable all mutating tools (create, update, delete). Only read operations will be available.

Alternatively, set GITLAB_SAFE_MODE=true for a dry-run mode: mutating tools remain visible but return a structured JSON preview instead of executing. Useful for auditing, training, or reviewing what an AI assistant would do.

Both Community Edition (CE) and Enterprise Edition (EE). Set GITLAB_TIER=premium or GITLAB_TIER=ultimate in stdio mode to enable additional tools for Premium/Ultimate features (DORA metrics, vulnerabilities, compliance, etc.); leave it unset to detect the tier from the instance license (fallback free). In HTTP mode, --tier can force the tier, otherwise it is detected per token+URL pool entry from the license.

The server includes retry logic with backoff for GitLab API rate limits. Errors are classified as transient (retryable) or permanent, with actionable hints in error messages.

Any MCP-compatible client: VS Code + GitHub Copilot, Claude Desktop, Cursor, Claude Code, Windsurf, JetBrains IDEs, Zed, Kiro, and others. The built-in setup wizard can auto-configure most clients.

Building from Source

git clone https://github.com/jmrplens/gitlab-mcp-server.git
cd gitlab-mcp-server
make build

The published container image is ghcr.io/jmrplens/gitlab-mcp-server:latest. See the Development Guide for cross-compilation, Docker Compose, and contributing guidelines.

Privacy Policy

The server runs entirely on your machine and has no telemetry, analytics, or backend of its own — data flows only between your MCP client and the GitLab instance you configure (plus an optional signed-binary update check against GitHub Releases). Your token is used solely to authenticate GitLab requests and is never logged. Full details: PRIVACY.md.

Contributing & Security

• Contributing: see CONTRIBUTING.md for development guidelines, branch naming, commit conventions, and the PR process.

• Security: see SECURITY.md for the security policy and vulnerability reporting.

• Code of Conduct: see CODE_OF_CONDUCT.md (Contributor Covenant v2.1).

Repository mirror: GitHub is the canonical repository. A read-only mirror is available on GitLab.com for discoverability; please open contributions on GitHub.

File counts

Functions

Ratios worth noting

Code patterns

Project

Hall of fame

Because why not