nds-mcp

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nds_get_constant

Retrieve a specific CODATA fundamental constant by name to get its value, with optional case-sensitive matching. Ideal for quick physical constant lookups.

Instructions

Get one CODATA fundamental constant by name (case-insensitive by default).

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>",
      "case_sensitive": "<case_sensitive>"
    },
    "name": "nds_get_constant"
  }
}

Input Schema

Name	Required	Description	Default
`name`	Yes	CODATA constant name (e.g. "Planck constant", "speed of light in vacuum")
`case_sensitive`	Yes	Whether to require exact case-sensitive name matching

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Aug 9, 2026

TDQS

A4/5.0

Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It adds the useful trait of case-insensitive matching by default, but it does not disclose what happens if the constant is not found, the return format (e.g., value and units), or any error behavior. This is a basic yet incomplete disclosure.

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, front-loaded sentence that immediately conveys the action and target. Every word is meaningful, with no filler or redundancy.

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?

The tool is simple with only two required parameters, both fully documented in the schema. The description provides the core purpose and a behavioral nuance, which is sufficient for a straightforward lookup. However, the absence of an output schema means the agent does not know the return structure, so it is not a 5.

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 description coverage is 100% for both parameters (name and case_sensitive), with examples and defaults provided. The description adds no additional parameter-level meaning beyond what the schema already contains, so baseline 3 is appropriate.

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 uses a specific verb ('Get') and clearly identifies the resource ('one CODATA fundamental constant') and the retrieval method ('by name'). It distinguishes itself from siblings like nds_list_constants, which lists constants, by focusing on single-constant retrieval.

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 implies the tool is used when you need a specific constant by name, which provides clear context. However, it does not explicitly mention when not to use it or name alternatives, so it falls just short of full guidance.

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