The tools.py module

Summary

Functions

execute_python_code	Execute Python code in the persistent Python session with automatic rule generation.
create_custom_plot	Create a custom plot using Matplotlib or PyVista in the persistent Python session.

Description

Common tool implementations for PyAnsys MCP servers.

This module provides reusable tool functions that product-specific MCP servers can use or extend. These are not registered tools themselves, but functions that can be called from product-specific tool implementations.

Module detail

async tools.execute_python_code(ctx: fastmcp.Context, code: str, timeout: int = 60) → str

Execute Python code in the persistent Python session with automatic rule generation.

This function should be used for custom Python code execution. When code execution fails, it automatically generates a rule using LLM analysis to prevent similar errors in the future.

Parameters:

ctxContext

MCP context containing server session and application context.

codestr

Python code to execute.

timeoutint, default: 60

Maximum time in seconds to allow for code execution.

Returns:

str

Execution result or error message. Returns JSON for structured output compatible with both stdio and http transports.

Examples

Execute simple Python code:

code = '''
result = sum([i**2 for i in range(10)])
print(f"Sum of squares: {result}")
'''
await execute_python_code(ctx, code)

Execute code with automatic rule generation on failure:

code = "result = 1/0"  # This will fail
await execute_python_code(ctx, code)

Automatically adds rule like: {"Division Operations": ["Do not divide by zero"]}

tools.create_custom_plot(ctx: fastmcp.Context, plot_code: str, plot_type: str = 'matplotlib', timeout: int = 60) → list[mcp.types.TextContent | mcp.types.ImageContent] | str

Create a custom plot using Matplotlib or PyVista in the persistent Python session.

Parameters:

ctxContext

MCP context containing server session and application context.

plot_codestr

Python code for creating the plot. You should use matplotlib.pyplot or PyVista. For Matplotlib, the code should create the figure/plot but NOT call plt.show(). Use the save_matplotlib_plot() or ``save_plot() helper functions to return the plot.

plot_typestr, default: “matplotlib”

Type of plot. Options are "matplotlib" or "pyvista".

timeoutint, default: 60

Maximum time in seconds for plot generation.

Returns:

list[TextContent | ImageContent]

List containing: - TextContent with the plot creation status message - ImageContent with the base64-encoded image data if successful or a JSON string with error details if failed.

Examples

Create a custom Matplotlib line plot:

plot_code = '''
import matplotlib.pyplot as plt
import numpy as np

# Extract data from MAPDL
displacements = mapdl.get_array("NODE", item1="U", it1num="Y")

# Create custom plot
plt.figure(figsize=(10, 6))
plt.plot(displacements)
plt.xlabel("Node Number")
plt.ylabel("Displacement (m)")
plt.title("Custom Displacement Plot")
plt.grid(True)
# Save and return
result = save_matplotlib_plot(dpi=150)
print(result)
'''

create_custom_plot(ctx, plot_code, plot_type="matplotlib")