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Onshape MCP Server

by hedless
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Python
Remote

create_linear_pattern

Repeats selected CAD features in a straight line within Onshape by specifying distance, instance count, and axis direction.

Instructions

Create a linear pattern of features

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoPattern nameLinear pattern
countNoTotal number of instances
distanceYesDistance between instances in inches
directionNoPattern direction axisX
elementIdYesPart Studio element ID
documentIdYesDocument ID
featureIdsYesFeature IDs to pattern
workspaceIdYesWorkspace ID
reapplyFeaturesNoRe-run the patterned features per instance (Onshape's 'Reapply features'). Turn on if the pattern fails with PATTERN_SWITCH_TO_PER_INSTANCE because the patterned body was later filleted, chamfered or booleaned

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.4.0
    • addedInput schema / properties / reapplyFeatures
      Added value: +{
+  "default": false,
+  "description": "Re-run the patterned features per instance (Onshape's 'Reapply features'). Turn on if the pattern fails with PATTERN_SWITCH_TO_PER_INSTANCE because the patterned body was later filleted, chamfered or booleaned",
+  "type": "boolean"
+}
  2. First observedv0.3.0

TDQS

C2.9/5.0
Behavior2/5

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

There are no annotations, so the description must disclose behavioral traits itselfainer. It only states 'Create a linear pattern of features' and does not explain that this mutates the Part Studio, what side effects occur, whether instances are recomputed, or what happens if the pattern fails. The schema hints at reapplyFeatures behavior, but the description itself adds almost no behavioral context.

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?

The description is a single front-loaded sentence with no filler words. It efficiently states the core action and resource. However, it is concise to the point of being sparse; it earns its place but could have used another sentence for usage or behavior without becoming bloated.

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?

This is a mutation tool with 9 parameters, 5 required, no annotations, and no output schema, but the description is only one sentence. It does not explain prerequisites, expected outcome, return behavior, or when to choose this over related pattern tools. The schema covers parameter meaning, but the tool definition is not complete enough for an agent to confidently invoke it in context.

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 100%, so the baseline is 3 even though the description adds little parameter detail. The description's 'features' aligns with the featureIds parameter and 'linear' hints at direction/distance, but it does not go beyond what the schema already documents. The schema carries the parameter-semantics burden here.

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?

The description 'Create a linear pattern of features' clearly identifies a specific verb and resource: it creates a pattern from existing features. The adjective 'linear' distinguishes it from the sibling 'create_circular_pattern', though the differentiation is implicit rather than explicit. It is not a pure tautology because it adds 'features' as the patterned object.

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?

The description gives no guidance on when to use this tool versus alternatives. It does not mention that it is appropriate for linear repetition along an axis, nor does it contrast with create_circular_pattern for radial repetition. An agent must infer usage entirely from the tool name and parameter schema.

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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