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Kratos MCP Server

kratos_get_variable_info

Check if a Kratos variable exists in the live build and get its type, resolving components like DISPLACEMENT_X to their array variable before using names in ProjectParameters.

Instructions

Look up specific Kratos variables by name in the live build: whether each exists and its type (double, array_1d_3, bool, int, vector, matrix, string, flags ...). Vector components such as DISPLACEMENT_X resolve to their array variable ('component_of'). Use it to check names before putting them in ProjectParameters (variable_name, output variables, nodal_solution_step_data_variables).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
namesYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.9.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and 'look up ... whether each exists and its type' plus the non-obvious 'component_of' resolution ('DISPLACEMENT_X resolves to its array variable') give real behavioral context beyond a restatement. It still omits what happens for unknown names and whether an active session/installation is required.

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

Conciseness4/5

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

Front-loads the essential lookup semantics and ends with a concrete usage directive; the enumerated type list adds useful vocabulary. Slightly dense but every sentence carries information.

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 single-parameter lookup with an output schema already covering the return shape, the description supplies purpose, usage context and the component_of nuance. The only real gap is error/failure behavior for names that do not exist.

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

Parameters3/5

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

Schema description coverage is 0%, so the description must compensate. It clarifies that the parameter is a variable name and that lookup is by name, but never states that multiple names can be passed at once (the schema key is 'names'), leaving batching semantics to inference.

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?

States a specific verb and resource ('Look up specific Kratos variables by name') plus scope ('in the live build'), and the type-resolution detail distinguishes it from kratos_list_variables, which only enumerates names.

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?

Gives an explicit when-to-use: check names before putting them in ProjectParameters (variable_name, output variables, nodal_solution_step_data_variables). It names concrete downstream consumers, though it does not name the sibling alternative (kratos_list_variables) or state when-not to use it.

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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