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lzinga

US Government Open Data MCP

by lzinga

cdc_places_city

Read-onlyIdempotent

Retrieve city-level CDC PLACES health measures for U.S. cities. Get obesity, diabetes, smoking, and 30+ indicators in one row per city.

Instructions

Get city-level health indicators from CDC PLACES — obesity, diabetes, smoking, depression, sleep, blood pressure, mental health, and 30+ more measures for every U.S. city with population > 50,000. Each row contains ALL measures for a city as separate columns (e.g. obesity_crudeprev, diabetes_crudeprev).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoCity name (partial match): 'Los Angeles', 'Chicago'
limitNoMax records (default 200)
stateNoTwo-letter state code: 'NY', 'CA', 'TX'

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2026.9.14
    • addedInput schema / properties / limit / default
      Added value: +200
  2. Changed1 schema field changedv2026.4.11
    • removedInput schema / additionalProperties
      Removed value: -false
  3. First observedv2026.3.9

TDQS

A3.7/5.0
Behavior3/5

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

Annotations include 'readOnlyHint: true' and 'destructiveHint: false', so the safety profile is covered. The description goes beyond annotations by explaining the output structure: 'Each row contains ALL measures for a city as separate columns'. This is useful context that annotations don't provide. However, it does not mention pagination behavior, rate limits, or data update frequency, which might be useful. Without those, the score is moderate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with two sentences. The first sentence is informative and front-loads the main purposeches. The second sentence adds a crucial detail about the data structure. There is minimal waste, though it could be slightly more structured with bullet points for the measures. Overall, it is efficient and readable.

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?

The tool is a read-only data retrieval tool with a simple interface (3 optional parameters). The description covers the main purpose, the data scope, and the output format. There is no output schema, so the description's explanation of the row structure is important and provided. The tool is not overly complex, so the description is adequate. Could benefit from noting the default limit behavior (default 200) which is in the schema anyway.

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 coverage is 100%, so all three parameters (city, limit, state) are documented in the schema. The description does not add substantial information about parameters beyond what the schema already states. For example, the description does not explain how to use 'state' with 'city' (e.g., whether state is needed for disambiguation). It mentions examples of city names in the schema, but the description does not enhance this. Since coverage is high, baseline is 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 a specific verb ('Get'), a specific resource ('city-level health indicators from CDC PLACES'), and the scope (all U.S. cities with population > 50,000). It lists examples of the measures included (obesity, diabetes, etc.). While there is a sibling 'cdc_places_health' which might be related, the description's specification of 'city-level' distinguishes it from the broader 'health' tool. The description is clear enough for an agent to understand what this tool does.

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

Usage Guidelines3/5

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

The description does not explicitly state when to use this tool versus alternatives.can be inferred that this tool is for city-level data, while sibling 'cdc_places_health' might cover other geographies, but no explicit comparison is made. It says 'every U.S. city' but does not mention when not to use it or suggest alternatives. The usage context is implied but not explicitly stated.

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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