Quick start#

Launch PyFluent-MCP#

The simplest way to start the MCP server is the ansys-fluent-mcp console script or the ansys.fluent.mcp module:

ansys-fluent-mcp

# equivalent
python -m ansys.fluent.mcp

It launches the server over STDIO (the default MCP transport) and waits for connections from MCP clients.

To run over streamable HTTP instead:

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

Connect to your IDE or client#

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

  • Claude Code (recommended for AI-assisted development)

  • Visual Studio Code with Copilot (for Visual Studio Code users)

  • Claude Desktop (macOS app)

  • Cursor and other MCP-compatible clients

Follow the basic workflow#

Connect to Fluent#

There are two ways to connect to Fluent once the MCP server is running.

Option 1: Launch a new Fluent session (recommended).

Ask your AI assistant to use the connect tool:

“Connect to Fluent and launch a new solver session.”

This starts a new Fluent process through PyFluent and connects to it automatically.

Option 2: Attach to an existing instance.

Ask your AI assistant to use the connect tool with IP and port:

“Connect to Fluent on localhost port 18500.”

This option is useful when Fluent is already running on a remote machine.

Inspect, generate, and execute#

Once Fluent is connected, the recommended loop for most setup tasks is:

  1. Discover: Use find_api, get_state, or list_named_objects to inspect the live settings tree.

  2. Validate: Use validate_code to pre-check Python snippets against the AST sandbox.

  3. Execute: Use run_code to apply the change to the live solver.

  4. Verify: Use summarize_setup or simulation_report to confirm the result.

Use offline-only tools#

You can use several tools without a live Fluent session:

  • find_api searches the bundled settings schema.

  • get_help returns per-path help text.

  • validate_code performs an AST pre-check only.

Consider example use cases#

  • Set up boundary conditions and solver settings with AI guidance.

  • Inspect mesh quality and cell counts on a loaded case.

  • Compare two case files to see what changed between versions.

  • Generate and debug PyFluent settings-API scripts interactively.

Next steps#