Provides an integration layer between CST Studio Suite and MCP, enabling automated MCP workflows and Trae-based configuration.
Configuration
View docs{
"mcpServers": {
"bbl21-cst_mcp": {
"command": "uv",
"args": [
"--directory",
"...\\\\CST_MCP",
"run",
"advanced_mcp.py"
]
}
}
}You will set up and run a CST MCP integration that connects CST Studio Suite with the Model Center Platform (MCP) using a Python-based package. This MCP server enables running a CST-related MCP workflow within an automated environment, leveraging uv to manage the virtual environment and startup. It supports importing configuration into Trae and validating MCP execution within the Trae IDE workflow.
You will use an MCP client to start and manage the CST MCP workflow through a local or remotely hosted MCP runner. The recommended approach leverages the uv package manager to manage the virtual environment and launch the MCP script. You can configure Trae to import an MCP setup, then verify and run a simple workflow to ensure the integration works end to end.
To start the MCP, you configure a startup entry that uses uv to run the advanced_mcp.py script from your project directory. This ensures the MCP starts inside the uv-managed virtual environment with all dependencies installed.
{
"mcpServers": {
"cst_interface": {
"command": "uv",
"args": [
"--directory",
"...\\CST_MCP",
"run",
"advanced_mcp.py"
]
}
}
}Follow these concrete steps to install and prepare the MCP server environment.
Prerequisites you need before starting:
Option A: Using uv (recommended)
Clone the repository and set up the environment with uv, then install dependencies.
# Clone the repository
git clone <repository-url>
cd CST_MCP
# Create and activate virtual environment
uv venv
# Activate (Windows, PowerShell)
.venv\Scripts\activate
# Activate (macOS/Linux)
source .venv/bin/activate
# Install dependencies via uv
uv add .Option B: Using traditional pip (alternative)
Clone the repository, create and activate a virtual environment, then install in editable mode.
# Clone the repository
git clone <repository-url>
cd CST_MCP
# Create virtual environment
python -m venv .venv
# Activate the virtual environment
# Windows:
.venv\Scripts\activate
# macOS/Linux:
source .venv/bin/activate
# Install dependencies in editable mode
uv pip install -e .Configuration details and common issues are addressed to help you get running quickly. You will manage the MCP startup via a JSON configuration and verify the setup in Trae.
Material definitions are provided in the Materials directory to support CST Studio Suite simulations and MCP workflows. Ensure CST Studio Suite 2026 is installed in the default location and that the project path references are correct.
If you encounter issues, check that your Python version matches the required version, and verify the Python version listed in the project configuration file is consistent with your environment.
The project uses a Python package that integrates CST Studio Suite with MCP and includes a JSON-based startup configuration to run the MCP in the uv-managed environment.
{
"mcpServers": {
"cst_interface": {
"command": "uv",
"args": [
"--directory",
"...\\CST_MCP",
"run",
"advanced_mcp.py"
]
}
}
}Common issues include the CST Studio Suite path not being found and Python version compatibility. Ensure CST Studio Suite 2026 is installed in the default location and verify the path in the configuration is correct. Confirm you are using Python 3.13 or higher, and check the recommended version in the .python-version file.
If you need to install uv, you can run: pip install uv on Windows, macOS, or Linux, or install uv via your preferred package manager as shown in the installation steps.
Package manager used to create and manage virtual environments and start MCP processes.
IDE used to import MCP configuration and manage MCP workflows.
MCP launcher script invoked by uv to start the CST MCP workflow.