reference-data-mcp-server

Physical Constant Lookup

ref_constant_lookup

Read-only

Look up a fundamental physical constant by name, symbol, or common alias. Returns the CODATA 2022 value, SI unit expression, relative standard uncertainty, and a short description. Recognizes common names and symbols — "speed of light", "c", "Avogadro's number", "N_A", "Planck", "h", "Boltzmann", "k_B" all resolve correctly. Fuzzy matching returns the closest match plus alternatives.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`query`	Yes	Constant name, symbol, or common alias (e.g., "speed of light", "c", "Avogadro", "N_A", "Planck constant", "h").

Output Schema

TableJSON Schema

Name	Required	Description
`name`	No	Full CODATA constant name.
`unit`	No	SI unit expression (e.g., "m s⁻¹", "J K⁻¹", "dimensionless").
`error`	No	Present when the call failed. Absent on success.
`exact`	No	True when the constant has an exact defined value (no experimental uncertainty).
`value`	No	Numeric value in SI units.
`symbol`	No	Standard mathematical symbol.
`related`	No	Related constants that also matched the query.
`codata_id`	No	CODATA identifier string, or null if not in CODATA registry.
`description`	No	Short description of the constant and its significance.
`uncertainty`	No	Absolute standard uncertainty in SI units. Null for exactly-defined constants.
`match_strategy`	No	How this constant was matched: exact_symbol = case-sensitive symbol hit (e.g. "G"), exact_name = exact alias/name match, fuzzy = partial or contains match. fuzzy signals the query was imprecise and the result is the closest candidate.
`dataset_version`	No	Data source version (CODATA year).
`uncertainty_relative`	No	Relative standard uncertainty or "exact (defined)" for exact values.

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 20, 2026

TDQS

A4.7/5.0

Behavior5/5

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

The description goes well beyond the readOnlyHint annotation by specifying the exact return contents (CODATA 2022 value, SI unit expression, relative standard uncertainty, short description) and the fuzzy-matching fallback behavior. It also confirms that both common names and symbols resolve correctly, which is useful behavioral information.

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?

Three sentences front-load the core purpose, then state outputs, then give useful examples and the fuzzy fallback. Every sentence adds information; there is no filler or redundancy.

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 single-parameter read-only lookup tool with an output schema, the description covers the query format, acceptable inputs, return contents, and edge-case behavior. Nothing essential is missing for an agent to select and invoke the tool correctly.

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% and the schema already documents the query parameter with examples. The description adds value by explaining alias recognition and fuzzy matching, giving the agent a more accurate model of what query strings will work.

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 names a specific verb ('look up'), resource ('fundamental physical constant'), and query forms ('name, symbol, or common alias'). It is clearly distinguishable from sibling tools like ref_element_lookup and ref_geo_lookup because the domain is explicit and illustrated with concrete constant examples.

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 makes the use case clear: any time an agent needs a fundamental physical constant and its CODATA 2022 value or uncertainty. It does not explicitly say when to prefer a sibling tool, but the domain distinction is strong enough that the agent can infer the correct context.

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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