Skip to main content
Glama
Sign In
fusion-mcp

fusion-mcp

by hellstein-dev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

measure_distance

Calculate the minimum distance in millimeters between two entities or points, returning the closest points on each for dimension checks and clearance analysis.

Instructions

Minimum distance between two entities or points, in mm.

Each operand is a ref from another tool or a point [x, y, z] in mm. Returns {"distance_mm", "point_a_mm", "point_b_mm"}: the closest points on each operand (null when Fusion does not report them).

Example: measure_distance(a="", b="") -> height.

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": {
      "a": "<a>",
      "b": "<b>"
    },
    "name": "measure_distance"
  }
}

Input Schema

NameRequiredDescriptionDefault
aYesAn entity ref (e.g. a face, edge, vertex, body, origin:XY) or a point [x, y, z] in mm
bYesAn entity ref (e.g. a face, edge, vertex, body, origin:XY) or a point [x, y, z] in mm

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the burden well: it gives units, describes the return fields, and discloses that closest points may be null when Fusion does not report them. It does not explicitly say the operation is read-only, but the measurement framing strongly implies it.

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 compact and front-loaded: purpose and units first, operand format second, return structure third, and a concrete example last. Every sentence contributes useful information.

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 two-parameter measurement tool with no output schema, the description supplies the essential context: units, operand forms, return fields, null behavior, and an example. An agent has enough information to invoke it correctly.

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 coverage is 100% and both parameters are fully documented in the schema. The description restates operand types and adds a useful example, but it does not add substantial meaning beyond the structured parameter descriptions.

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 states a specific measurement operation, its resource (minimum distance between entities or points), and its unit (mm). It is clearly distinguishable from siblings such as measure_angle and inspect_bounding_box.

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 gives clear context for use: two operands, each either an entity ref or an [x, y, z] point in mm, with an example of measuring height between faces. It does not explicitly name when to prefer alternatives, but the measurement context is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools