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MCP Server for Element

A Model Context Protocol (MCP) server that provides AI assistants (Agents) with access to Siemens Element design system and component API documentation through Retrieval-Augmented Generation (RAG). This enables more accurate and relevant assistance with design system and component library APIs.

Usage and use cases

  • Local MCP server installation includes all design system documentation, component APIs, examples and icon information
  • MCP server integration with your AI Agent setup of choice, integrated into your IDE (for example, GitHub Copilot Agent integration within VS Code with project-related MCP configuration)
  • Use cases include (but are not limited to):
  • Get design system best practice information
  • Export components
  • Review project text according to UX writing guidelines
  • Generate new pages using design system components
  • Add and modify pages

Installation

Prerequisites

  • Node.js (20+ recommended)
  • Access to the API https://api.siemens.com/llm by creating a free token at https://my.siemens.com with llm scope. We use the embeddings API. Siemens access is required to request a token. We are working on a configurable alternative.
  • IDE/Agent/LLM setup of your choice (for example: VS Code, GitHub Copilot, Claude Sonnet 4.5)

Version selection

We distribute a MCP server package @siemens/element-mcp for every @siemens/element-ng version. The version of @siemens/element-mcp must match your version of @siemens/element-ng. The version number of the MCP package @siemens/element-mcp is a combination of the @siemens/element-ng version and the version of the MCP code.

For example, @siemens/element-mcp@48.2.0-v.1.4.8 comes with the data of @siemens/element-ng@48.2.0 and v.1.4.8 is the version of the MCP script.

To facilitate the version selection, we use npm distribution tags @element<version> that match the version of @siemens/element-ng. When using the corresponding distribution tag on installation, you get the latest version of the MCP package that matches your @siemens/element-ng version and simplifies handling in your package.json.

"dependencies": {
    "@siemens/element-ng": "48.2.0",
  },
  "devDependencies": {
    "@siemens/element-mcp": "48.2.0-v.1.4.8",
  }

New MCP package versions on the same element-ng version are incremented like 48.2.0-v.1.4.9, 48.2.0-v.1.4.10, 48.2.0-v.1.5.0.

Project installation

npm install --save-dev --save-exact @siemens/element-mcp@element48.2.0

# Or with yarn
yarn add -D --exact @siemens/element-mcp@element48.2.0

Global installation

npm install -g @siemens/element-mcp@element48.2.0

Upgrading

Simply install the tag for your version and framework again:

# in project
npm install --save-dev --save-exact @siemens/element-mcp@element48.3.0

# with yarn
yarn add -D --exact @siemens/element-mcp@element48.3.0

# global
npm install -g --save-exact @siemens/element-mcp@element48.3.0

Quick Start

After local project or global package installation, you need to initialize the MCP server and provide the access token.

  1. Navigate to your project directory:
cd your-project
  1. Run initial setup:
npx @siemens/element-mcp init

Or if token is already set up:

npx @siemens/element-mcp setup

Important: Run this command in the root of every project where you want to use the MCP server.

  1. Follow the prompts:
  2. Enter your LLM token from https://my.siemens.com/ (requires 'llm' scope)
  3. This token is needed to generate embeddings for semantic search of the documentation. The embeddings help find relevant documentation chunks, but the actual LLM (language model) that processes your queries and generates responses is provided separately by your AI tool (e.g., GitHub Copilot, Claude, etc.)
  4. Choose which tools to configure (VS Code, Cline, Zed, etc.)
  5. Optionally set up Element instruction files for AI agents

  6. The tool will create MCP configuration files based on your selection, commit the local configuration to share it (make sure it is not ignored by .gitignore)

  7. Restart your AI tools (VS Code, Cline, Zed, etc.)

  8. Ensure the server is running and trust the MCP server, e.g. click the "Server" icon in the Github Copilot Chat panel in VS Code.

  9. For GitHub Copilot in VS Code: Make sure you are in Agent Mode (not Chat Mode). Use models like Claude Sonnet 4.5.

  10. Start prompting:

  11. "How do I use the Filtered-Search component from @siemens/element-ng?"
  12. "Show me examples of @siemens/charts-ng usage"
  13. "Implement a dashboard with different widgets"
  14. "Find icons related to AI or machine learning"
  15. "Review the texts of this project"

The MCP server starts automatically when your AI tools need it.

Setup Options

During init or setup, select which configuration(s) to create:

  • Local VS Code / GitHub Copilot (Repository) creates a VS Code MCP configuration file at .vscode/mcp.json in the current repository
  • Cline Global Settings updates global Cline MCP configuration
  • VS Code / GitHub Copilot Global Config writes user-level MCP config
  • Zed Global Settings configures Zed editor / agent MCP

AI Agent Instructions (optional)

After MCP configuration, you can set up Element and Angular instruction files so AI agents work more effectively with your codebase. Do this in each repository where you want instructions.

You have two options:

  • Symbolic link to receive updates
    Keeps files synced with the installed package. Requires the package to remain installed and may not work on all systems or package managers. The tool can create symlinks automatically; otherwise, create links yourself pointing to the installed package's AGENTS.md and Element instructions.

  • Copy the content Copy the contents of the package’s AGENTS.md into one of the following in your repo:

  • .github/instructions/Element.instructions.md
  • AGENTS.md
  • .github/copilot-instructions.md

If you prefer manual copy, open the package’s AGENTS.md, then paste it into your chosen file and commit it. Repeat per repository whenever you want to update the instructions.

Logging

Per default no logging is performed, but you can enable local-only logging of all search queries and retrieval results during setup.

Manually enabling logging

In your MCP configuration add the flag --log to log all search queries and retrieval results to local log files in ~/.element-mcp.

{
  "servers": {
    "@siemens/element-mcp": {
      "type": "stdio",
      "command": "npx",
      "args": ["@siemens/element-mcp", "--log"]
    }
  }
}

Viewing and sharing logs

To view logs, use the npx @siemens/element-mcp log command, select any relevant session and look at the output or the files copied to your current working directory.

For feedback about the MCP and Agent results, please create an issue at https://code.siemens.com/ux/sdl-mcp/issues, share your information, and include the relevant logs.

Usage

Commands

Init (First-time setup)

Complete initial setup: configure token and create all MCP configurations.

npx @siemens/element-mcp init

Setup (Update configurations)

Create or update MCP configuration files for your tools (uses existing token).

npx @siemens/element-mcp setup

Setup Token

Set or update only the LLM token in system keychain.

npx @siemens/element-mcp setup-token

Check

Verify your installation and configuration.

npx @siemens/element-mcp check

Test

Test the MCP server with a sample query.

npx @siemens/element-mcp test

Log

Check your previous MCP retrieval logs (if enabled / not disabled).

npx @siemens/element-mcp log

Use within WSL (Windows Subsystem for Linux)

If you're using WSL, you need to configure the LLM token using environment variables instead of the system keychain. Before running any commands, add the following to a .env file in the project root (if you're using project installation):

SDL_MCP_TOKEN_ENV=true
OPENAI_API_KEY=<your-key-here>

Make sure the .env file is in your .gitignore and can't be committed.

Alternatively, or if you're using global installation, add these to your shell profile (~/.zprofile or ~/.bash_profile):

export SDL_MCP_TOKEN_ENV=true
export OPENAI_API_KEY=<your-key-here>

Connection Issues

  • Verify that the MCP server is running (it should start automatically)
  • Restart your AI tool after configuration changes
  • Verify your LLM token is valid at https://my.siemens.com/

Manual Configuration

If you prefer to set up the configurations manually, here are the required files and their contents.

VS Code (.vscode/mcp.json or User/mcp.json)

{
  "servers": {
    "@siemens/element-mcp": {
      "type": "stdio",
      "command": "npx",
      "args": ["@siemens/element-mcp"]
    }
  }
}

Cline (Global Cline MCP settings)

{
  "mcpServers": {
    "@siemens/element-mcp": {
      "command": "npx",
      "args": ["@siemens/element-mcp"]
    }
  }
}

Zed (Global Zed settings)

{
  "context_servers": {
    "@siemens/element-mcp": {
      "source": "custom",
      "command": "<path-to-npx, run which/where npx to find>",
      "args": ["@siemens/element-mcp"],
      "env": {}
    }
  }
}

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