Coolprop

Coolprop Fluid Properties

coolprop_fluid_properties

Read-onlyIdempotent

Thermophysical properties of a pure fluid, computed from two independent state variables (PropsSI-style — give e.g. temperature + pressure, get density, enthalpy, entropy, viscosity, thermal conductivity, specific heat, phase, ...). Covers ~124 fluids (water, refrigerants, hydrocarbons, cryogens, ...) via CoolProp (open-source, MIT), computed in-process rather than looked up from a table — valid over each fluid's full equation-of-state range, not just tabulated points. No aliases: call coolprop_list_fluids for exact names (e.g. "CarbonDioxide", not "CO2").

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "fluid": "Water",
      "outputs": [
        "D",
        "H",
        "S",
        "VISCOSITY",
        "CONDUCTIVITY",
        "Phase"
      ],
      "input1_name": "T",
      "input2_name": "P",
      "input1_value": 298.15,
      "input2_value": 101325
    },
    "name": "coolprop_fluid_properties"
  }
}

Input Schema

Name	Required	Description
`fluid`	Yes	Exact CoolProp fluid name, e.g. "Water", "Nitrogen", "R134a", "CarbonDioxide" — see coolprop_list_fluids for the full list (no aliases)
`outputs`	Yes	Property codes to compute, up to 12 per call: T, P, D (density kg/m3), H (enthalpy J/kg), S (entropy J/kg/K), U (internal energy J/kg), Q (vapor quality), CPMASS (isobaric specific heat J/kg/K), CVMASS (isochoric specific heat J/kg/K), VISCOSITY (Pa·s), CONDUCTIVITY (W/m/K), PRANDTL, M (molar mass kg/mol), Phase (liquid/gas/supercritical/twophase/...)
`input1_name`	Yes	First independent state variable code: T (temperature, K), P (pressure, Pa), D (mass density, kg/m3), H (mass enthalpy, J/kg), S (mass entropy, J/kg/K), U (mass internal energy, J/kg), or Q (vapor quality, 0-1)
`input2_name`	Yes	Second independent state variable code — must differ from input1_name. Same code set as input1_name.
`input1_value`	Yes	Value for input1_name, SI units
`input2_value`	Yes	Value for input2_name, SI units

Output Schema

Name	Required	Description	Default
`fluid`	No
`inputs`	No
`source`	No
`outputs`	No
`failed_outputs`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 26, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already cover read-only, idempotent, non-destructive behavior. The description adds meaningful behavioral context: properties are computed in-process from CoolProp equations of state rather than looked up from a table, valid over each fluid's full range, covering about 124 fluids. It does not discuss invalid-state or phase-boundary failure behavior, which keeps it below 5.

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 purpose is front-loaded, followed by coverage, computational model, and the fluid-naming caveat. Every sentence earns its place; the parenthetical property examples clarify rather than pad.

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?

The tool is scientifically complex, but the description covers the input model, fluid naming, coverage, and computation model. An output schema exists and annotations cover the safety profile, so no essential agent-facing context is missing.

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

Parameters4/5

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

Schema coverage is 100%, so the schema already documents each parameter thoroughly. The description adds a useful conceptual model beyond the schema: PropsSI-style pairing of two independent state variables, plus the critical no-alias naming constraint.

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 action and resource: compute thermophysical properties of a pure fluid from two independent state variables. It explicitly distinguishes itself from the sibling by saying to call coolprop_list_fluids for exact fluid names, so an agent can select it without opening the schema.

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?

It gives clear usage context (provide two state variables, request property outputs) and names the relevant alternative for fluid-name resolution. It does not explicitly describe when not to use it, but for this specialized computation tool the guidance is strong.

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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