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MCPFax Public-Data Utility API

Sunrise / sunset

v1_sun
Read-onlyIdempotent

Sunrise / sunset: Sunrise, sunset, solar noon, day length by coordinate. Source: sunrise-sunset.org / Open-Meteo. $0.005 per call · GET /v1/sun

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoPlace name (alternative). Example: 'Cairo'.
latNoLatitude. Example: '34.05'.
lonNoLongitude. Example: '-118.24'.
dateNoYYYY-MM-DD (default today). Example: '2026-06-21'.

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare the operation read-only, idempotent, and non-destructive, lowering the burden on the description. The description adds useful context: the upstream sources, the per-call cost, the GET endpoint, and the returned fields. It does not mention response timezone or location-precedence behavior, but the schema covers the default date and the annotations cover safety.

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 extremely compact and well front-loaded: the returned values appear immediately, followed by source, pricing, and endpoint. Every clause carries useful information and there is no redundant filler.

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?

For a simple read-only tool with zero required parameters and full schema coverage, the description provides enough for an agent to infer the result categories. The lack of an output schema is partially offset by listing the returned fields. A minor gap is the absence of timezone conventions or how the q parameter interacts with lat/lon, but these are not blocking.

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%, so all four parameters are already documented with types and examples. The description adds almost no parameter-specific meaning beyond hinting that location is coordinate-based. Baseline 3 is appropriate because the schema is doing the semantic work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies the resource—sunrise, sunset, solar noon, and day length—and specifies that it works by coordinate. It goes beyond the title by listing the exact computed fields and the data source. It does not use an explicit action verb like 'get' or 'retrieve', and it does not actively distinguish itself from time/weather siblings, but the meaning is clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance about when to use this tool versus v1_timezone, v1_weather, v1_geocode, or v1_holidays. The intended use case is implied by the name and field list, but the description never states the conditions under which this tool is the right choice.

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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TDQS

A3.7/5.0
Disambiguation5/5

Every tool targets a distinct resource or operation—geocoding, weather, DNS, VIN, stock quotes, etc.—with no meaningful overlap in purpose. Even the location- and finance-related tools are clearly separated by their descriptions.

Naming Consistency5/5

All tools follow the same v1_<resource>[_modifier] snake_case pattern, such as v1_air_quality, v1_reverse_geocode, and v1_validate_email. Although the names are not verb-based, the convention is perfectly consistent across all 31 tools.

Tool Count2/5

31 tools exceeds the 25+ threshold and creates a heavy selection burden for agents, even though the server's stated purpose is broad. Many endpoints are small single-purpose lookups that could be grouped into fewer combined tools without losing clarity.

Completeness4/5

As a general public-data utility, the set covers a wide range of common lookup categories: location, weather, finance, legal, health, business, internet, and reference data. It has minor gaps like historical financial time series or phone-number validation, but no obvious dead ends since all tools are self-contained read-only lookups.

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