Quick start#

Launch PyCFX-MCP#

Use the ansys-cfx-mcp console script to quickly start PyCFX-MCP:

ansys-cfx-mcp

This script starts PyCFX-MCP over STDIO, the default MCP transport, and waits for MCP client connections.

To run over Streamable HTTP instead:

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

Connect to your IDE or client#

PyCFX-MCP works with multiple MCP-compatible clients. For setup information, see IDE and client configuration.

  • Use Claude Code for AI-assisted development.

  • Use Visual Studio Code with Copilot.

  • Use Claude Desktop.

  • Use Cursor or another MCP-compatible client.

Follow the basic workflow#

Connect to CFX#

Use one of these methods to connect to CFX after PyCFX-MCP starts.

Option 1: Start a local CFX app.

Ask your AI assistant to use the connect tool:

“Connect to CFX and start a local PyCFX backend.”

This prepares the PyCFX backend so routed workflow actions can start or connect to CFX-Pre, CFX-Solver, and CFD-Post sessions as needed.

Option 2: Attach to an existing PyCFX server.

Ask your AI assistant to use the connect tool with an IP address, port, password, or server information file:

“Connect to CFX on localhost port 18500.”

This option is useful when a PyCFX service is already running on another machine or was started outside the MCP client.

Inspect, route, and execute#

After CFX connects, use this loop for most setup and analysis tasks:

  1. Discover: Use session_status and cfx_model_context to inspect the active backend, model names, API paths, and state snippets.

  2. Route: Use cfx_workflow for supported lifecycle actions such as importing meshes, writing solver input, starting a solver, waiting for completion, and opening CFD-Post results.

  3. Generate: Use codegen only when you need custom PyCFX Python that is not already covered by a routed workflow.

  4. Validate: Use validate_code to pre-check generated snippets against the AST sandbox.

  5. Execute: Use run_code to run reviewed snippets against the active CFX backend.

Use offline-capable tools#

Use these tools before you connect to a live CFX app:

  • session_status: Reports that no backend is connected and lists available tools.

  • codegen: Returns deterministic recipe snippets for supported CFX tasks and can use optional LLM fallback when configured.

  • validate_code: Performs an AST pre-check without mutating a CFX session.

  • clarify: Asks for missing information before a workflow or code generation request proceeds.

Consider example use cases#

  • Start CFX-Pre and import a mesh with AI guidance.

  • Write a solver input file and run a steady-state solver workflow.

  • Locate the generated results file and open it in CFD-Post.

  • Generate and validate small PyCFX snippets for custom inspection or edits.

Next steps#