Skip to main content
Glama

MCPFax Public-Data Utility API

Business-day math

v1_business_days
Read-onlyIdempotent

Business-day math: Count business days in a range, or add/subtract N business days, skipping weekends & holidays. Source: computed + Nager.Date. $0.005 per call · GET /v1/business-days

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNoEnd date (count mode). Example: '2026-01-31'.
daysNoOffset in business days (offset mode; may be negative). Example: '10'.
startYesStart date YYYY-MM-DD. Example: '2026-01-02'.
countryNoISO alpha-2 for holidays (default US). Example: 'US'.

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds useful context beyond those annotations by mentioning the computation source (Nager.Date), the per-call cost, and the HTTP endpoint, which helps the agent understand external dependencies and pricing.

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 compact, front-loaded with the core purpose, and every part earns its place. The source, cost, and endpoint are included without clutter.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple and the schema covers parameters well, but there is no output schema and the description does not state the return shape, explain inclusive/exclusive date behavior, or clarify what happens when only 'start' is provided without 'end' or 'days'. These are real but minor gaps.

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?

Input schema coverage is 100%, so the schema already documents every parameter clearly. The description adds a useful high-level explanation of the two modes, but does not meaningfully extend parameter meaning beyond what the schema properties already state.

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 resource ('business days') and specific operations ('Count business days in a range, or add/subtract N business days'), which distinguishes it from sibling tools like v1_holidays. It is specific and not a tautology of the tool name.

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 gives clear context for when to use the tool: counting business days in a range or applying a business-day offset. It does not explicitly name alternatives or exclusions, but the mode split ('count mode' vs 'offset mode') is enough to guide correct use.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

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.

Resources