Quick start#

Learn how to connect PyLumerical-MCP to your preferred agentic AI client. Before you begin, install PyLumerical-MCP by following the instructions in Installation.

Connect to your agentic client#

You can use PyLumerical-MCP with transport over both Streamable HTTP and STDIO.

Since PyLumerical-MCP uses the open source MCP standard, which enables AI applications to seamlessly integrate with external systems, you can use it with a wide range of agent-based frameworks and agent harnesses that support MCP.

The following sections show you the important settings for PyLumerical-MCP. For instructions on how to connect, see your preferred client’s documentation.

Configure Streamable HTTP transport#

To configure Streamable HTTP transport, you can set it through the .env file.

  1. Copy the .env.example template file and rename it to .env.

  2. Set the following variables:

    • FASTMCP_TRANSPORT: Set to "streamable-http".

    • FASTMCP_HOST: Set to the hostname for the server. For local use, set to "127.0.0.1".

    • FASTMCP_PORT: Set to the port for the server, such as 8081.

  3. Start the MCP server by running ansys-lumerical-mcp from the command line in the environment where the MCP server is installed.

  4. Connect to the MCP server from your client.

Configure STDIO transport#

The configuration for STDIO transport depends on your specific client. However, these general guidelines can help:

  • Set the target executable to the ansys-lumerical-mcp in the environment where it is installed.

  • Set the transport type to stdio. The specific key can vary by client.

  • Leave the argument field empty.

View additional resources#

Usage examples

View example prompts for using PyLumerical-MCP to drive Lumerical tools.

Usage examples
User guide

Learn how to use PyLumerical-MCP effectively.

User guide
Available tools

Access references for every tool the server exposes.

The tools.py module