CDC Open Data

The CDC's data products: disease surveillance (notifiable conditions, FluView), vital statistics (births, deaths), behavioral risk factors (BRFSS), environmental health, social determinants of health. The authoritative US public-health data. Free, no auth (some datasets require a free token for higher volume).

Part of Pipeworx — an MCP gateway connecting AI agents to 1394+ live data sources.

Why this matters for AI agents

For US public-health questions — disease incidence, mortality rates, behavioral risk factors, environmental exposures — CDC is canonical. Government-grade methodology, transparent data documentation. Pair with WHO Global Health Observatory for international comparisons.

Common flows:

• Notifiable diseases. Weekly counts by state, condition (TB, salmonella, measles, etc.).
• Mortality stats. Death counts by cause, demographic, geography. NVSS data going back decades.
• BRFSS. Behavioral Risk Factor Surveillance System — state-level prevalence of smoking, obesity, diabetes, mental health, etc.
• Flu / respiratory virus surveillance. Weekly FluView, plus COVID-era respiratory illness reporting.

Auth

Most CDC datasets are open via Socrata's data.cdc.gov platform; free, lightly rate-limited. For sustained volume, get a free Socrata app token. Pass via _apiKey.

Datasets worth knowing

Dataset	Cadence	Use
NVSS Mortality	Annual / monthly	Death counts and rates by cause/age/sex/race/state
FluView	Weekly	Flu activity surveillance
NNDSS (National Notifiable Disease Surveillance)	Weekly	Reportable diseases by state
BRFSS	Annual	State-level risk-factor prevalence
YRBSS (Youth Risk Behavior)	Biennial	Adolescent health behaviors
NHANES	Continuous	Examination + lab data, smaller representative sample

For "what's the rate of X in state Y?" most answers come from NVSS (mortality) or BRFSS (risk factors).

Common pitfalls

• Suppression for small counts. CDC suppresses cells with <10 deaths or low denominators to protect privacy. The dataset returns null/asterisk; don't treat as zero.
• Crude vs age-adjusted rates. Mortality rates per 100k are usually reported as both. Age-adjusted are comparable across populations with different age structures; crude aren't.
• Race/ethnicity handling. CDC race categories shifted post-2003 (multi-race added). Time-series across the break needs care.
• State of residence vs occurrence. Mortality data reports both. Most analyses want residence (where the person lived); some want occurrence (where the death certificate was filed). Read the metadata.
• Pandemic-era anomalies. 2020-2022 mortality data has classification issues (COVID coding, excess-mortality interpretation). Long-term trends should annotate the disruption.
• Real-time CDC data is delayed. Weekly FluView ~1-2 week lag. Monthly notifiable diseases ~1 month. NVSS mortality ~6-12 month lag. Plan agent flows accordingly.

Quick Start

Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):

{
  "mcpServers": {
    "cdc": {
      "url": "https://gateway.pipeworx.io/cdc/mcp"
    }
  }
}

Or connect to the full Pipeworx gateway for access to all 1394+ data sources:

{
  "mcpServers": {
    "pipeworx": {
      "url": "https://gateway.pipeworx.io/mcp"
    }
  }
}

Using with ask_pipeworx

Instead of calling tools directly, you can ask questions in plain English:

ask_pipeworx({ question: "your question about Cdc data" })

The gateway picks the right tool and fills the arguments automatically.

More

• Docs and guides
• pipeworx.io

License

MIT