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COMSOL MCP Server

COMSOL MCP Server

by Zhangyoupeng1996
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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results_plots_list

Lists all plot nodes defined in a COMSOL model, enabling quick identification of available visualizations.

Instructions

List all plot nodes defined in a model.

Args: model_name: Model name (default: current model)

Returns: List of plot node names

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "results_plots_list"
  }
}

Input Schema

NameRequiredDescriptionDefault
model_nameNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior2/5

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

No annotations are provided, and the description does not disclose any behavioral traits such as side effects, error handling, or that it is a read-only operation. The description is too minimal.

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

Conciseness5/5

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

The description is concise with no wasted words. The Args and Returns section is clearly formatted and provides necessary information without redundancy.

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

Completeness4/5

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

For a simple list operation with one optional parameter and no output schema, the description is adequate. It could be improved by noting what happens when model_name is invalid, but it covers the essentials.

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

Parameters4/5

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

The description adds value to the schema by explaining the default behavior ('default: current model') and the meaning of the optional model_name parameter, which is not present in the schema.

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

Purpose5/5

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

The description clearly states the action (list), the resource (plot nodes), and the scope (in a model). It distinguishes well from sibling tools like results_exports_list and datasets_list.

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

Usage Guidelines3/5

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

The description implies usage when you need to retrieve plot nodes, but there is no explicit guidance on when to use this vs alternatives or any preconditions.

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

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