Ansys CFX-MCP

Ansys CFX-MCP (ansys-cfx-mcp) is a Model Context Protocol (MCP) server that enables AI assistants to interact with Ansys CFX through PyCFX. It enables natural-language-assisted CFX-Pre, CFX Solver, and CFD-Post workflows for setup, execution, and postprocessing.

It is built on PyAnsys Common MCP (ansys-common-mcp), the shared PyAnsys MCP foundation.

This package is self-contained and works as a standalone server for any MCP host. It exposes a compact CFX-oriented tool surface so you can connect to CFX sessions, inspect bounded model context, validate and run reviewed PyCFX snippets, and coordinate common solver and CFD-Post actions.

For quick-start, configuration, architecture, examples, and per-tool reference material, see the PyCFX-MCP documentation.

Overview

Ansys CFX-MCP is a stateless MCP leaf. MCP clients such as Visual Studio Code Copilot, Claude Desktop, Cursor, or a custom automation host call a focused set of tools to drive live CFX-Pre, CFD-Post, and CFX Solver sessions. Custom Python runs through a validated, Python-level restricted execution path. This is not an operating-system or container sandbox.

Key features:

• CFX session management: Start or attach to CFX-Pre, CFX Solver, and CFD-Post workflows.

• Workflow routing: Use one compact cfx_workflow tool for common CFX lifecycle actions.

• Bounded model context: Inspect summaries, named objects, API help, allowed values, and selected state snippets without dumping entire models into an MCP client.

• Validated execution: Run custom snippets in a persistent PyCFX execution context with strict AST validation, guarded imports, and limited built-in functions.

• Flexible MCP transport: Run over STDIO for local clients or Streamable HTTP for trusted local integrations.

Tool surface

The default MCP surface includes seven tools:

The server also exposes a toolsets://definition MCP resource for clients or conductors that group related tools. The default CFX toolsets cover connection management, CFX workflow routing, CFX model context, and code execution.

Requirements

PyCFX and Ansys CFX are required for live-session tools. Any tool that touches a CFX app (connect, run_code, cfx_workflow, cfx_model_context, and session_status) requires ansys-cfx-core and a licensed CFX installation on your machine.

Installation

Install the latest release for users:

pip install ansys-cfx-mcp

Install the latest release for developers:

git clone https://github.com/ansys/pycfx-mcp.git
cd pycfx-mcp
pip install -e ".[dev,doc]"

Usage

Run PyCFX-MCP over STDIO, the default transport for desktop MCP clients:

ansys-cfx-mcp --transport stdio

Or, run PyCFX-MCP over Streamable HTTP:

ansys-cfx-mcp --transport http --host 127.0.0.1 --port 8000

Use STDIO for desktop MCP clients that launch the server process. Use Streamable HTTP only on trusted networks or behind infrastructure that provides authentication and TLS.

Starting PyCFX-MCP only makes the tools available. You still need an MCP-compatible client, such as Visual Studio Code Copilot, Claude Desktop, Cursor, or another assistant host, to connect to PyCFX-MCP. For more information, see IDE and client configuration in the PyCFX-MCP documentation.

Configuration

The standalone server does not call a language model. Configure only the server transport, logging, and backend options needed for your MCP client. Custom code authoring belongs in the MCP host or a higher-level agent layer; PyCFX-MCP validates and runs reviewed Python through validate_code and run_code.

For transport settings, see Configuration in the PyCFX-MCP documentation.

License

This project is licensed under the Apache License, Version 2.0. See the LICENSE file for details.

Resources

• PyCFX-MCP documentation

• PyCFX package

• PyAnsys documentation

• Model Context Protocol documentation

• FastMCP documentation

• Ansys CFX product information

• PyCFX-MCP Issues page

• PyCFX-MCP Discussions page

For general PyAnsys questions, email pyansys.core@ansys.com.