Skip to main content
Glama
sinagilassi

PyThermoCalcDB-NASA-MCP

by sinagilassi

calc_dH_rxn_STD

Calculate the standard enthalpy change of a chemical reaction using the NASA-9 database. Specify the reaction equation, components, states, and temperature for accurate thermodynamic data.

Instructions

Calculate standard enthalpy change of reaction using the embedded NASA-9 database by default, or caller-supplied reference_content when source='reference'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYesRequest for a reaction NASA property calculation.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It mentions the default database and the option for reference content, but it does not disclose whether the tool is read-only or destructive, error behavior, or performance characteristics. The description adds context about data sources beyond the schema, but behavioral details are minimal.

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 a single sentence that front-loads the core purpose and effectively conveys both default behavior and optional customization. Every word earns its place without any fluff.

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 complexity of the input schema (nested objects, multiple enums) and the presence of an output schema, the description is concise yet adequate for an agent to understand when to use source='reference'. It could benefit from mentioning that the output provides the enthalpy value and units, but the output schema presumably covers that.

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 description coverage is 100%, so the baseline is 3. The description adds value by clarifying the role of reference_content and the source parameter, which govern whether to use the embedded database or external YAML. This context helps the agent understand when to provide reference_content, going beyond what the schema enumerates.

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 calculates the standard enthalpy change of reaction, specifying the default data source (embedded NASA-9 database) and the alternative source (reference_content when source='reference'). This distinguishes it from sibling tools like calc_dS_rxn_STD and calc_dG_rxn_STD, which likely compute other thermodynamic quantities.

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 implicitly tells the agent when to use this tool (for standard enthalpy calculations) and when to use source='reference' (for custom data). However, it does not explicitly exclude scenarios where other tools like calc_G_T or calc_Keq would be more appropriate, though sibling tool names provide some differentiation.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/sinagilassi/PyThermoCalcDB-NASA-MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server