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COMSOL MCP Server

COMSOL MCP Server

by Zhangyoupeng1996
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

study_solve_async

Initiate asynchronous solving of a study in COMSOL Multiphysics, monitor progress with study_get_progress and cancel with study_cancel.

Instructions

Start solving a study in the background (asynchronous).

Use study_get_progress to monitor progress and study_cancel to stop.

Args: study_name: Study to solve (None for all studies) model_name: Model name (default: current model)

Returns: Confirmation that solving started, or error message

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": "study_solve_async"
  }
}

Input Schema

NameRequiredDescriptionDefault
study_nameNo
model_nameNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It explains the async nature and that it returns a confirmation or error, but does not detail potential side effects, permissions, or state changes. Still, it covers the key behavioral traits adequately.

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: three sentences plus an Args section. It front-loads the core purpose and immediately provides usage guidance. No unnecessary words, well-organized.

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

Completeness5/5

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

Given the simplicity (2 optional parameters, no output schema), the description is complete. It explains the async workflow and references sibling tools (study_get_progress, study_cancel) to complete the lifecycle. No gaps remain.

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?

Schema description coverage is 0%, but the description includes an Args section that explains both parameters: study_name (study to solve, None for all) and model_name (default current model). This adds meaningful context, though model_name could elaborate on valid values or format.

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 verb 'Start solving' and the resource 'study', and specifies the asynchronous mode. It distinguishes from sibling 'study_solve' by explicitly mentioning 'asynchronous', and references related tools for monitoring and cancellation.

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

Usage Guidelines4/5

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

The description provides immediate next steps: use study_get_progress for monitoring and study_cancel to stop. However, it does not explicitly state when to use this async version versus the synchronous study_solve, which would be helpful for decision-making.

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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