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lzinga

US Government Open Data MCP

by lzinga

epa_uv_index

Read-onlyIdempotent

Get UV index forecasts for any U.S. ZIP code or city/state. Use the UV scale to assess sun exposure risk and guide health recommendations.

Instructions

Get UV index forecast for a U.S. location (ZIP code or city/state). UV Scale: 0-2 Low, 3-5 Moderate, 6-7 High, 8-10 Very High, 11+ Extreme. Useful for health recommendations -- high UV correlates with skin cancer risk.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
zipNo5-digit ZIP code: '10001', '90210'. Use this OR city+state.
cityNoCity name: 'Los Angeles', 'Chicago'. Must be used with state.
stateNoTwo-letter state code: 'CA', 'IL'. Must be used with city.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2026.4.11
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observedv2026.3.9

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and non-destructive behavior. The description adds the UV scale (0-2 Low, 3-5 Moderate, etc.) and the health relevance, which are not present in annotations or schema. This enriches the agent's understanding beyond the structured metadata without contradicting it.

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 three short sentences, front-loading the core purpose, then adding the interpretive scale and a practical usage note. There is no redundant wording; every sentence earns its place, making it highly concise and well-structured.

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?

With no output schema, the description compensates by providing the UV scale, which implies the return is a numeric index that can be mapped to categories. It does not specify forecast period or behavior when no parameters are provided, but given the simple nature and strong annotations, this is largely sufficient for an agent to call the tool correctly.

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%, with each parameter (zip, city, state) already clearly described. The description only mentions 'ZIP code or city/state', which is already implicit in the schema. No additional parameter semantics are provided, so it rests at the baseline of 3.

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 tool fetches a UV index forecast for a U.S. location, specifying both the resource and action. It is distinct from all sibling tools, none of which deal with UV index. The inclusion of the UV scale further clarifies the exact output interpretation.

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 notes it is for U.S. locations and ties usage to health recommendations, giving a clear context. It does not explicitly mention alternatives or when not to use it, but given the extensive sibling list, no other tool serves this purpose, so the guidance is adequate though not explicit about exclusions.

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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