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gpambrozio

onshape-mcp

by gpambrozio

List Part Studio features

onshape_get_features
Read-only

Get the full feature tree with each feature's ID, type, parameters, and regeneration state. Ideal when you need detailed feature-level information instead of just the final geometry.

Instructions

The full feature tree with each feature's id, type, parameters and regeneration state. Large — prefer onshape_measure or onshape_get_parts when you only need the result of the tree.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
wsYesWorkspace id — the <ws> segment of the document URL.
docYesDocument id — the <doc> in cad.onshape.com/documents/<doc>/w/<ws>/e/<elem>.
elemYesElement id (tab) — the <elem> segment of the document URL.
configurationNoEncoded configuration string from onshape_encode_configuration.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already provide readOnlyHint=true, so no safety contradiction. The description adds the behavioral context that the output is large and includes regeneration state, which is useful. However, it does not disclose pagination, rate limits, or any specific response format, but given the readOnly annotation, additional behavior is less critical. A 3 is appropriate for adequate but not rich behavioral disclosure.

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?

Two sentences, zero waste. The first sentence states the core functionality, and the second immediately provides routing guidance. The warning about size is front-loaded and helps the agent avoid expensive calls. Excellent structure with no extraneous text.

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?

For a read-only list tool with complete schema coverage and no output schema, the description provides everything needed: what it returns, when to use alternatives, and the size warning. The lack of output schema is fine since the description enumerates the major fields (id, type, parameters, regeneration state). Nothing critical is missing.

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 schema fully documents all four parameters. The description does not add any parameter-specific meaning, but with complete schema coverage, baseline 3 is correct. The description only mentions the 'configuration' indirectly as part of the feature tree, but no extra syntax or constraints are needed.

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 tool lists the full feature tree, including id, type, parameters, and regeneration state. It names specific sibling tools (onshape_measure, onshape_get_parts) as alternatives, distinguishing it from those that return results rather than the tree. This is specific and actionable.

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

Usage Guidelines5/5

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

The description explicitly says to prefer onshape_measure or onshape_get_parts when only the result of the tree is needed, providing clear when-to-use vs. when-not-to-use guidance. It also warns about the large size of the output, which helps the agent decide based on cost. This is excellent routing guidance.

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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