Getting started#

Introduction#

PyAnsys Common MCP is a foundational library that helps you build Model Context Protocol (MCP) servers. These servers let AI assistants interact with Ansys products through PyAnsys libraries.

This section shows how to create your first MCP server in under 30 minutes. For architectural concepts and advanced patterns, see the User guide.

Target audience: PyAnsys library developers who create MCP servers for their products.

Installation#

Here are the requirements for PyAnsys Common MCP:

Requirements#

  • Python 3.10 or later (up to 3.14)

  • A PyAnsys library for your product (such as PyMAPDL or PyFluent)

Install in user mode#

The ansys.common.mcp package currently supports Python 3.10 through Python 3.14 on Windows, Mac OS, and Linux.

Install the latest package for use with this command:

pip install ansys-common-mcp

Alternatively, install the latest PyAnsys Common MCP GitHub package with this command:

pip install git+https://github.com/ansys/pyansys-common-mcp.git

Install in developer mode#

If you want to contribute to PyAnsys Common MCP or create custom servers, install in developer mode:

# Clone the repository
git clone https://github.com/ansys/pyansys-common-mcp.git
cd pyansys-common-mcp

# Install in editable mode with development dependencies
pip install -e .[dev]

# Or install documentation dependencies for building documentation
pip install -e .[doc]

Verify the installation#

Verify the installation by importing the package:

>>> from ansys.common.mcp import PyAnsysBaseMCP, PyAnsysBaseAppContext
>>> from ansys.common.mcp import PersistentPythonSession

Quick start#

Refer to the PyExample-MCP section for a step-by-step example. Below is a high-level overview of the steps to create a simple MCP server using the pyansys-common-mcp library.

  1. Define the context: Create a custom context class that inherits from ansys.common.mcp.context.PyAnsysBaseAppContext.

  2. Implement the server: Create a server class that inherits from ansys.common.mcp.server.PyAnsysBaseMCP and implements the product_startup() and product_cleanup() methods.

  3. Add tools: Implement one or more tools in the server to provide specific functionality.

  4. Initialize the package: Create an __init__.py to initialize the package and import necessary components.

  5. Create the entry point: Define the entry point for the server in src/pyexample_mcp/__main__.py.

  6. Configure the package: Set up the package configuration in pyproject.toml.

  7. Run the server: Install the package and run the server using the entry point.

The server starts and communicates using stdio. It is ready to accept MCP requests from AI clients.

Next steps#

Your MCP server is ready. Explore these sections: