Overview#

What is PyMAPDL-MCP?#

Use PyMAPDL-MCP as a bridge between AI assistants and Ansys MAPDL. It uses the Model Context Protocol (MCP) to expose PyMAPDL capabilities as standardized tools that AI systems can call.

What is MCP?#

MCP is a standardized interface for connecting AI systems to external tools and data sources. It allows AI assistants to perform the following tasks:

  • Discover available tools and their capabilities.

  • Call tools with structured parameters.

  • Receive results and error information.

  • Maintain state across multiple interactions.

How does MCP work?#

  • Client connection: An MCP-compatible client (such as Claude) connects to the PyMAPDL-MCP server.

  • Tool discovery: The client discovers available tools for controlling MAPDL.

  • Tool execution: The client calls tools with appropriate parameters.

  • Result return: The server returns results or errors to the client.

  • Interaction loop: The cycle continues for the duration of the session.

Understand the architecture#

PyMAPDL-MCP includes several key components:

  • MCP server: Implements the MCP protocol and handles client connections.

  • Tool registry: Maintains the list of available tools.

  • PyMAPDL integration: Wraps PyMAPDL capabilities as MCP tools.

  • Session management: Manages MAPDL instance lifecycle.

  • Context management: Maintains app state across interactions.

Explore use cases#

Automated simulations

Use AI to design and run parametric FEA studies automatically.

Interactive analysis

Ask an AI assistant to analyze simulation results and suggest improvements.

Documentation generation

Automatically create reports and documentation from simulations.

Script debugging

Get AI assistance in debugging complex MAPDL scripts.

Learning tool

Use an AI assistant as a tutor for learning MAPDL and FEA concepts.

Next steps#