Ansys CFX-MCP
OfficialEnables AI assistants to interact with Ansys CFX, supporting CFX-Pre, CFX Solver, and CFD-Post workflows for setup, execution, and postprocessing.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Ansys CFX-MCPSet up a CFX-Pre simulation for flow over a NACA 0012 airfoil"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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, generate small PyCFX snippets, validate code, 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. Your LLM host, such as Visual Studio Code Copilot, Claude Desktop, Cursor, or a custom agent, calls 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_workflowtool 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.
Deterministic-first codegen: Generate PyCFX-oriented snippets from bundled CFX recipes first, with an optional server-side LLM fallback only for unmatched
codegenprompts.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.
Related MCP server: Ansys MCP Server
Tool surface
The default MCP surface includes nine tools:
Group | Tools |
Connection and session |
|
CFX workflow routing |
|
Bounded model context |
|
Code generation and execution |
|
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, code generation, and code
execution.
Requirements
Requirement | When needed | Notes |
Python 3.12 or later | Always | 3.12, 3.13 and 3.14 are supported |
Core runtime dependencies | Always (installed automatically) |
|
A licensed local Ansys CFX installation | To launch or attach CFX tools | Required for workflows that use CFX-Pre, CFX Solver, or CFD-Post |
Optional LLM fallback | Only for unmatched | Native providers through the LiteLLM SDK with |
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, andsession_status) requiresansys-cfx-coreand a licensed CFX installation on your machine.
Installation
Install the latest release for users:
pip install ansys-cfx-mcpInstall 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 stdioOr, run PyCFX-MCP over Streamable HTTP:
ansys-cfx-mcp --transport http --host 127.0.0.1 --port 8000Use 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 default server needs no LLM configuration. The codegen path first applies
guardrails and deterministic CFX recipes. If no recipe matches, only the
codegen tool can fall through to the optional server-side LLM fallback.
The cfx_workflow, cfx_model_context, validate_code, and run_code tools
do not call an LLM.
To enable the optional model- and provider-agnostic LLM fallback or tune TLS and 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
For general PyAnsys questions, email pyansys.core@ansys.com.
Maintenance
Resources
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