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self-host-fusion360-mcp

self-host-fusion360-mcp

by mystify59
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

fusion_set_parameter

Idempotent

Update a parameter by setting its expression to resize parametric models. Specify the parameter name and a formula or value, such as '25 mm' or 'width * 2'.

Instructions

Set a parameter's expression, e.g. '25 mm' or 'width * 2'. This is the preferred way to resize an existing parametric model.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>",
      "expression": "<expression>"
    },
    "name": "fusion_set_parameter"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes
expressionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

A4/5.0
Behavior3/5

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

Annotations already indicate idempotentHint=true, openWorldHint=true, and readOnlyHint=false. The description adds that it modifies a parameter's expression, consistent with annotations, but does not elaborate on side effects or error handling. It provides moderate additional context.

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, no fluff. First sentence defines action with examples, second sentence provides usage guidance. Every word earns its place.

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?

Given the tool's simplicity and strong annotations (idempotent, open world), the description covers the core purpose and preferred usage. It could mention that the parameter must exist, but overall it is sufficiently complete for an AI agent.

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?

With 0% schema description coverage, the description partially compensates by giving example expressions and indicating that 'name' refers to a parameter. However, it does not explain valid name sources or expression syntax details, leaving some ambiguity.

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 sets a parameter's expression, provides examples like '25 mm' or 'width * 2', and positions it as the preferred way to resize an existing parametric model, distinguishing it from sibling tools like fusion_create_parameter.

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 specifies this is the preferred way to resize an existing parametric model, giving clear context for when to use it. However, it does not explicitly mention when not to use it or provide alternative tools for other scenarios.

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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