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Query CDC Dataset

cdc.health.query
Read-onlyIdempotent

Query CDC health datasets by state, year, age group, or condition using SoQL filters. Get structured results with column names.

Instructions

Query a specific CDC dataset using SoQL filters — filter by state, year, age group, condition. Returns structured rows with column names. Supports WHERE, SELECT, ORDER, GROUP BY. Use cdc.datasets to find dataset IDs first (US Gov, Socrata SODA API)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataset_idYesCDC dataset ID in xxxx-xxxx format (e.g. "9bhg-hcku" for COVID deaths). Use cdc.datasets to find IDs.
whereNoSoQL WHERE clause filter (e.g. "state='CA'", "year > 2020", "age_group='65+'")
selectNoColumns to return, comma-separated (e.g. "state, year, deaths"). Default: all columns.
orderNoSort order (e.g. "year DESC", "deaths DESC"). Default: dataset default order.
groupNoGroup by columns for aggregation (e.g. "state" with select "state, SUM(deaths)")
limitNoMax rows to return (1-1000, default 100)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv1.5.0

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint: true and destructiveHint: false, so the description does not need to cover safety. It adds that the tool returns structured rows with column names and supports SoQL operations, which is useful but not essential given the annotations.

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?

Two sentences efficiently convey the action, filters, supported operations, and prerequisite tool. No extraneous information; front-loaded with the most critical details.

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 description covers the tool's purpose, usage pattern, and prerequisites. It mentions that results are structured rows with column names, and the presence of an output schema handles return format details. Could mention pagination or error handling, but overall sufficient.

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?

With 100% schema description coverage, the schema already thoroughly documents all 6 parameters with examples. The description adds high-level context about SoQL filters but does not provide new details beyond what the schema offers.

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 that the tool queries a specific CDC dataset using SoQL filters, listing filtering dimensions (state, year, age group, condition). It distinguishes itself from the sibling cdc.health.datasets by explicitly referencing it as a prerequisite for finding dataset IDs.

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 explicitly instructs users to use cdc.health.datasets first to find dataset IDs, providing clear prerequisite guidance. However, it does not explicitly state when NOT to use this tool or mention alternative query tools for different data sources.

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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