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API Hub MCP — 337+ Tools

API Hub MCP — 337+ Tools

by scotia1973-bot
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

density_calc

Solve for density, mass, or volume given any two known measurements.

Instructions

Calculate density, mass, or volume given any two values.

Parameters:
    mass — Mass (leave 0 if unknown).
    volume — Volume (leave 0 if unknown).
    density — Density (leave 0 if unknown).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "density_calc"
  }
}

Input Schema

NameRequiredDescriptionDefault
massNo
volumeNo
densityNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.4.1

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden. It explains that the tool computes the missing value from two provided ones. This is sufficient for a straightforward math tool, though edge cases (e.g., all non-zero) are not addressed.

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 brief (two sentences plus a parameter list) and front-loaded with the key purpose. Every line is necessary and adds value.

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 output schema exists (not shown but present), the description does not need to detail return values. It covers the essential usage for a simple tool, though it could mention how to interpret the result.

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

Parameters5/5

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

The schema has 0% description coverage, so the description must compensate. It explains each parameter (mass, volume, density) and the convention 'leave 0 if unknown,' which adds significant meaning beyond the schema.

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's purpose: 'Calculate density, mass, or volume given any two values.' It uses a specific verb and resource, and the context of sibling tools (e.g., force_calc) confirms it is distinct.

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 indicates when to use this tool: when two of the three values are known. It specifies to leave the unknown as 0, which provides clear guidance. However, it does not explicitly mention scenarios where all three are provided or negative values.

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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