GitLab MCP Server

A Model Context Protocol (MCP) server that exposes the entire GitLab API as MCP tools, resources, and prompts for AI assistants. Single static binary — zero dependencies.

Security first: Continuously monitored on SonarCloud with quality gates, coverage, and security scanning. Supports read-only mode, safe mode (dry-run preview), and self-hosted GitLab with TLS verification.

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

Token Footprint

Measured with go run ./cmd/gen_readme/ against the current base catalog. Totals estimate startup context visible to an MCP client: visible tool schemas plus shared resources and prompts, using the same byte/4 token heuristic as cmd/audit_tokens.

Default configuration: with TOOL_SURFACE unset or TOOL_SURFACE=dynamic, CAPABILITY_SURFACE=full, META_TOOLS unset, META_PARAM_SCHEMA=opaque, and GITLAB_ENTERPRISE unset or false, 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 (GITLAB_ENTERPRISE=false). META_PARAM_SCHEMA=opaque affects only visible meta-tool input schemas; dynamic mode gets exact action schemas from gitlab_find_action, and every surface advertises gitlab://tools plus gitlab://tools/{id} for on-demand action browsing and input schemas. Individual mode already exposes one schema per tool.

Highlights

• 1027 MCP tools on self-managed Enterprise/Premium, or 1033 on GitLab.com Enterprise/Premium with experimental Orbit Knowledge Graph support — broad GitLab REST API v4 + GraphQL coverage across 176 packages under internal/tools: projects, branches, tags, releases, merge requests, issues, pipelines, jobs, groups, users, wikis, environments, deployments, packages, container registry, runners, feature flags, CI/CD variables, security attributes, security categories, templates, admin settings, access tokens, deploy keys, Orbit, and more
• Default dynamic toolset — exposes only gitlab_find_action and gitlab_execute_action while keeping the same canonical GitLab action catalog. Optional domain meta-tools remain available with TOOL_SURFACE=meta: 33 base, 49 on self-managed Enterprise/Premium, or 50 on GitLab.com Enterprise/Premium
• AI model tool-use evaluation — automated schema-only and Docker-backed runs against populated GitLab CE and licensed Enterprise instances measure tool/action selection, parameter shaping, recovery from GitLab errors, and destructive-action safety across Anthropic, Google, OpenAI, and Qwen. Published summaries appear in the managed evaluation block below; see AI Model Evaluation Results
• 11 sampling actions — LLM-assisted code review, issue analysis, pipeline failure diagnosis, security review, release notes, milestone reports, and more via gitlab_analyze meta-tool (MCP sampling capability)
• 4 elicitation tools — interactive creation wizards (issue, MR, release, project) with step-by-step user prompts
• 46 MCP resources in default dynamic/full mode — read-only data: user, groups, group members, group projects, projects, issues, pipelines, members, labels, milestones, branches, MRs, releases, tags, commits, file blobs, wiki pages, MR notes, MR discussions, single-entity templates (issue, MR, branch, tag, release, label, milestone, commit, wiki page, deployment, environment, job, board, snippet, deploy key, feature flag, group label, group milestone), the surface-aware gitlab://tools manifest and gitlab://tools/{id} detail template, workspace roots, and 5 workflow best-practice guides
• 37 MCP prompts — AI-optimized: code review, pipeline status, risk assessment, release notes, standup, workload, user stats, team management, cross-project dashboards, analytics, milestones, Git workflow quality, audit
• 6 MCP capabilities — logging, completions, roots, progress, sampling, elicitation
• 50 tool icons — base64-encoded SVG icons (Sizes: ["any"]) on all tools, resources, and prompts for visual identification in MCP clients
• Pagination on all list endpoints with metadata (total items, pages, next/prev)
• Transports: stdio (default for desktop AI) and HTTP (Streamable HTTP for remote clients)
• Cross-platform: Windows, Linux & macOS, amd64 & arm64
• Self-hosted GitLab with self-signed TLS certificate support

Example Prompts

Once connected, just talk to your AI assistant in natural language:

"List my GitLab projects" "Show me open merge requests in my-app" "Create a merge request from feature-login to main" "Review merge request !15 — is it safe to merge?" "List open issues assigned to me" "What's the pipeline status for project 42?" "Why did the last pipeline fail?" "Generate release notes from v1.0 to v2.0"

The server handles the translation from natural language to GitLab API calls. You do not need to know project IDs, API endpoints, or JSON syntax — the AI assistant figures that out for you. See Usage Examples for more scenarios.

Quick Start

1. Get the server

Download the latest binary for your platform from GitHub Releases and make it executable:

chmod +x gitlab-mcp-server-*  # Linux/macOS only

Or pull the published container image:

docker pull ghcr.io/jmrplens/gitlab-mcp-server:latest

2. Configure GitLab access

Recommended: Run the built-in setup wizard — it configures your GitLab connection and MCP client in one step:

./gitlab-mcp-server --setup

Tip: The wizard supports Web UI, Terminal UI, and plain CLI modes. On Windows, double-click the .exe to launch the wizard automatically.

Manual setup only needs a GitLab Personal Access Token with api scope:

GITLAB_TOKEN=glpat-xxxxxxxxxxxxxxxxxxxx

GITLAB_URL defaults to https://gitlab.com; add it only when you connect to a self-managed GitLab instance.

GITLAB_URL=https://gitlab.example.com

3. Connect your MCP client

Most desktop clients use stdio: the client starts one local MCP server process and talks to it over stdin/stdout. Choose one of these runtime patterns.

Native binary (stdio)

VS Code and Cursor-style MCP configuration:

Add to .vscode/mcp.json in your workspace:

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

Claude Desktop uses the same server command under mcpServers:

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

For client-specific paths, secure token prompts, HTTP OAuth, and extra IDEs, see IDE Configuration.

Docker launched by an IDE (stdio)

If an IDE starts Docker as the MCP server process, keep docker run -i and pass --http=false after the image name. Do not publish port 8080 in this mode.

{
  "servers": {
    "gitlab": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "GITLAB_TOKEN",
        "-e",
        "GITLAB_URL",
        "-e",
        "GITLAB_SKIP_TLS_VERIFY",
        "ghcr.io/jmrplens/gitlab-mcp-server:latest",
        "--http=false"
      ],
      "env": {
        "GITLAB_TOKEN": "glpat-xxxxxxxxxxxxxxxxxxxx",
        "GITLAB_URL": "https://gitlab.com",
        "GITLAB_SKIP_TLS_VERIFY": "false"
      }
    }
  }
}

Docker or binary as an HTTP MCP server

Use HTTP mode for shared, remote, or multi-user deployments. The Docker image starts in HTTP mode by default, but the flags are shown explicitly here for clarity. These examples publish the container port on host loopback only; --http-addr=0.0.0.0:8080 binds inside the container.

# Fixed GitLab instance for all clients
docker run -d --name gitlab-mcp-server -p 127.0.0.1:8080:8080 \
  ghcr.io/jmrplens/gitlab-mcp-server:latest \
  --http \
  --http-addr=0.0.0.0:8080 \
  --gitlab-url=https://gitlab.com

# Multi-instance mode: clients send GITLAB-URL per request
docker run -d --name gitlab-mcp-server -p 127.0.0.1:8080:8080 \
  ghcr.io/jmrplens/gitlab-mcp-server:latest \
  --http \
  --http-addr=0.0.0.0:8080

HTTP clients authenticate each request with PRIVATE-TOKEN or Authorization: Bearer:

{
  "servers": {
    "gitlab": {
      "type": "http",
      "url": "http://localhost:8080/mcp",
      "headers": {
        "PRIVATE-TOKEN": "glpat-xxxxxxxxxxxxxxxxxxxx"
      }
    }
  }
}

In multi-instance mode, clients must also send GITLAB-URL. See HTTP Server Mode for OAuth, reverse proxy, rate limit, and server-pool details.

4. Verify

Open your AI client and try:

"List my GitLab projects"

See the Getting Started guide for detailed setup instructions.

Tool Modes

Three registration modes, controlled by TOOL_SURFACE:

For dynamic experiments where resources and prompts dominate initial context, set CAPABILITY_SURFACE=minimal (stdio) or --capability-surface=minimal (HTTP). Minimal keeps gitlab://workspace/roots plus the surface-aware gitlab://tools manifest so dynamic, meta, and individual deployments can still read accepted call shapes. The default remains full.

Dynamic mode is now the default low-token find/execute surface; see Dynamic Toolset for the field-aware ranking model, fuzzy fallback, response shapes, workflow diagrams, and migration guidance. Set TOOL_SURFACE=meta to use the consolidated domain meta-tool catalog.

The detailed meta-tool catalog now lives in Meta-Tools Reference, including action counts, Enterprise/Premium markers, and examples.

Compatibility

Tested with: VS Code + GitHub Copilot, Claude Desktop, Claude Code, Cursor, Windsurf, JetBrains IDEs, Zed, Kiro, Cline, Roo Code.

See the full Compatibility Matrix for detailed client support.

AI Model Tool-Use Evaluation

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

Current published result: Docker CE-on-Enterprise meta 20260527.

The published model-evaluation set covers 560 task attempts and 1096 expected MCP operations. Across the selected reports, models emitted 1109 tool calls over 1145 model requests, with 100.0% aggregate final success. See AI Model Evaluation Results for the detailed current matrix.

Current published result: Docker CE dynamic 20260606.

The published model-evaluation set covers 620 task attempts and 2292 expected MCP operations. Across the selected reports, models emitted 2367 tool calls over 2369 model requests, with 99.0% 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 20260605 (Enterprise).

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 available at jmrplens.github.io/gitlab-mcp-server. Use this map when you need the source-of-truth reference for a specific area:

Tech Stack

Building from Source

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

See the Development Guide for cross-compilation and contributing guidelines.

Container Image

The published image is ghcr.io/jmrplens/gitlab-mcp-server:latest. Runtime examples live in Quick Start next to MCP client configuration, and Docker Compose/source-build details live in the Development Guide.

FAQ

Contributing

See CONTRIBUTING.md for development guidelines, branch naming, commit conventions, and pull request process.

Security

See SECURITY.md for the security policy and vulnerability reporting.

Code of Conduct

See CODE_OF_CONDUCT.md. This project follows the Contributor Covenant v2.1.

Unnecessary Statistics

Numbers nobody asked for, but here they are anyway.

File counts

Functions

Ratios worth noting

Code patterns

Project

Hall of fame

Because why not