minimum-wage-mcp
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- AlicenseNot gradedqualityAmaintenanceProvides current, source-cited US minimum wage, tipped wage, and FLSA overtime data for AI agents, with tools to query rates, verify wage floors, and list scheduled changes. It refreshes state-level wage information from DOL sources and refuses to guess when data is unavailable.MIT
- FlicenseAqualityAmaintenanceEnables AI agents to query Japan's 47 prefectures' regional minimum wages from official MHLW statistics, including hourly rates, effective dates, and 24-year history.4-
- AlicenseAqualityDmaintenanceEnables AI assistants to compute US take-home pay, self-employment taxes, and capital gains taxes for the 2026 tax year using the engine from statetakehome.com.335 npmMIT
- AlicenseNot gradedqualityCmaintenanceEnables models to query real US government data (BLS, BEA, Census, IRS 2026) to calculate 2026 take-home pay across all 50 states plus DC, compare cost-of-living-adjusted salaries between 50 US metros, retrieve tax bracket ladders, and look up occupation-level salary percentiles. Exposes five read-only tools over a free, keyless remote Streamable HTTP endpoint.MIT
- AlicenseNot gradedqualityAmaintenanceEnables AI agents to calculate US household employer (nanny) taxes for all 50 states plus DC, including Social Security, Medicare, FUTA, and state unemployment, through natural language.MIT
- AlicenseNot gradedqualityAmaintenanceEnables AI assistants to plan and price household employment in Switzerland (cleaner, nanny, carer), returning hiring checklists with real deadlines, employer costs and net wages, minimum-wage checks, and rules for all 26 cantons through read-only tools. Every figure is tied to its official source document and verification date.CC BY-4.0
TDQS
Scored across 4 tools
Each tool targets a clearly distinct operation: single-state lookup, scheduled increases, multi-state comparison, and income calculation. There is no meaningful overlap, and the descriptions reinforce the boundaries (e.g., compare_states explicitly handles 2-10 states while get_minimum_wage handles one).
Three tools follow a clear verb_noun snake_case pattern (get_minimum_wage, list_upcoming_increases, compare_states). The fourth, annual_income_at_minimum_wage, is a descriptive noun phrase rather than a verb-led name, a minor deviation that remains readable and unambiguous.
Four tools is well-scoped for a focused minimum-wage dataset. Each tool serves a distinct query shape (single lookup, temporal listing, comparison, derived income) and none feels redundant or missing at this scale.
The surface covers lookup, forward-looking changes, comparison, and derived annual income, which addresses the core lifecycle for this domain. Minor gaps exist for broader use cases (e.g., historical rates, all-state listing beyond a 2-10 comparison, or locality-level data), but these are explicitly out of stated scope.