Tools and capabilities#

Tool availability#

PyMAPDL-MCP dynamically enables and disables tools based on whether an MAPDL instance is connected. This keeps the AI assistant’s context small when MAPDL is not in use.

Before connecting to MAPDL, you can access these tools:

Tool	Description
`check_mapdl_installed`	Check if MAPDL is installed on the system
`list_mapdl_instances`	Discover running MAPDL instances
`connect_to_mapdl`	Connect to an existing MAPDL instance
`launch_mapdl_session`	Launch and connect to a new MAPDL instance
`get_guidelines_for`	Workflow guidance and best-practice context tool

After connecting to MAPDL, you gain access to the full set of tools. When you call the disconnect_from_mapdl tool, the MAPDL-specific tools become unavailable.

Tool	Description
`check_mapdl_status`	Get comprehensive MAPDL status
`run_mapdl_command`	Execute a single MAPDL command
`run_multiple_commands`	Execute multiple MAPDL commands in batch
`disconnect_from_mapdl`	Disconnect from the MAPDL instance
`screenshot`	Capture the MAPDL graphics window
`run_python_code`	Execute Python/PyMAPDL code in a persistent session
`custom_plot`	Create custom matplotlib or PyVista plots

Note

When you use --connect-on-startup, MAPDL connects at startup and all tools are immediately available (except connect_to_mapdl, launch_mapdl_session, and disconnect_from_mapdl, which are locked).

Using the tools#

Running MAPDL commands#

Use run_mapdl_command for single commands:

“Run VPLOT on the MAPDL instance.”

For multiple commands, use run_multiple_commands, which uses MAPDL’s input_strings method for batch execution. This is significantly faster than running commands one by one:

“Run these commands: /PREP7, ET,1,SOLID185, MP,EX,1,200E9.”

Custom Python code execution#

Use run_python_code to execute arbitrary Python and PyMAPDL code in a persistent session:

“Execute this Python code: displacements = mapdl.get_array(‘NODE’, item1=’U’, it1num=’Y’); print(f’Max displacement: {displacements.max()}’).”

This is useful for:

Custom data processing and analysis
Advanced PyVista visualizations
NumPy/Pandas data manipulation
Complex computations not available through direct MAPDL commands

Creating custom plots#

Use custom_plot to create Matplotlib or PyVista plots that are not available in MAPDL’s native plotting:

“Create a Matplotlib plot showing nodal displacements versus node number.”

Important

custom_plot is for plots that MAPDL cannot produce natively. For standard MAPDL plots (APLOT, LPLOT, KPLOT, PLNSOL, etc.), use the MAPDL commands together with the screenshot tool.

Capturing plots#

After running a MAPDL plot command, use the screenshot tool to capture the graphics window:

“Show a plot of the geometry.”

“Capture the current MAPDL plot.”

It returns the image directly so the AI assistant can display it inline. Works with all MAPDL native plot commands, including:

Geometry: APLOT, LPLOT, KPLOT, VPLOT
Mesh: EPLOT, NPLOT
Post-processing: PLNSOL, PLESOL, PLDISP

Python code execution#

Run Python code: Execute arbitrary Python code in the persistent session (requires MAPDL connection).
Integrate with data analysis: Use NumPy, Pandas, and other Python libraries.

Workflow examples#

Linear static analysis#

Launch MAPDL instance.
Define geometry (blocks, cylinders, and so on).
Define materials and element types.
Mesh the geometry.
Apply boundary conditions and loads.
Run solution.
Extract and visualize results.

Parametric study#

Set up the base MAPDL model.
Define parameter ranges.
Update parameters, run analysis, and extract results for each parameter combination.
Analyze and plot parameter sensitivity.

Result postprocessing#

Run or load MAPDL analysis.
Extract result data.
Create custom visualizations.
Generate analysis reports.

Feature reference#

For the documentation of all available tools, including parameters and return values, see Tools reference.

Best practices#

For recommendations on using PyMAPDL-MCP effectively, see Best practices.