Mechanical MCP Server

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run_mechanical_script

Runs custom Python scripts inside the ANSYS Mechanical ACT API to automate geometry, mesh, boundary conditions, analysis solving, and report generation.

Instructions

Run custom Python script inside Mechanical ACT API. Args: script

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "script": "<script>"
    },
    "name": "run_mechanical_script"
  }
}

Input Schema

Name	Required	Description	Default
`script`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.1Oct 17, 2026

TDQS

C2.6/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations and no output/behavior notes, the description carries the full burden and mostly fails it. Executing arbitrary Python inside a CAE session is highly consequential — the description should disclose sandboxing, side effects on the model, required connection state, and error behavior. Only the phrase 'inside Mechanical ACT API' hints at execution context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded and very short, which is a virtue, but the trailing 'Args: script' fragment duplicates the parameter name and earns no space. Appropriate brevity tips into under-specification for an arbitrary-code-execution tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be explained here. But for a tool that runs arbitrary code against a live simulation model, the description omits execution environment, side effects, and any connection prerequisite — too thin given the tool's risk profile.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the single parameter has no description in the schema. The description's 'Args: script' merely restates the parameter name; the only real semantic added is that the string is Python source for the ACT API, with no syntax, entry-point, or expected-form guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource — running a custom Python script — and names the execution context (Mechanical ACT API), which separates it from the domain-specific siblings like add_force or generate_mesh. It stops short of contrasting itself with those siblings explicitly, but the purpose is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to reach for this tool versus the dozens of purpose-built siblings (add_fixed_support, set_mesh_element_size, etc.). No prerequisites, no indication of what the script can or cannot touch, and no exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.