CDC — Centers for Disease Control and Prevention

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 1683+ 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.
• Wastewater surveillance (NWSS). Weekly national or state SARS-CoV-2/flu/RSV viral activity level from sewershed sampling — the leading indicator ahead of case/hospitalization data, and the only way to answer "what's the current trend in wastewater levels?" wastewater_national_trend / wastewater_state_trend do this directly; don't route this question to search_datasets, whose full-text search on "wastewater"/"nwss" returns unrelated pollen/filovirus datasets instead.

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

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

NWSS wastewater viral activity level

wastewater_national_trend and wastewater_state_trend read atcp-73re ("CDC Wastewater Viral Activity Level for SARS-CoV-2, Influenza A and RSV"), published weekly on Fridays from ~800+ sewershed sites. It's site-level (one row per site per pathogen per week, each with a 5-level category — Very Low/Low/Moderate/High/Very High), so there is no ready-made national or state figure: both tools compute a population-weighted mean of the category rank (1..5) across every reporting site for the grain requested, plus a week-over-week trend (rising/declining/stable, ±0.15 threshold on the weighted score). pathogen accepts loose aliases (covid, flu, rsv); state accepts postal abbreviations (CA) as well as full names.

CDC previously published two "NWSS Public ..." datasets (g653-rqe2, 2ew6-ywp6) with a national percentile metric; both stopped updating in Aug 2026 and are now dead ends — CDC replaced them with the per-pathogen raw qPCR datasets (j9g8-acpt SARS-CoV-2, ymmh-divb Influenza A, 45cq-cw4i RSV) and the classified atcp-73re these tools use. Verify before assuming otherwise: curl 'https://data.cdc.gov/resource/atcp-73re.json?$select=max(week_end)'.

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"
    }
  }
}

What this endpoint actually serves

tools/list at https://gateway.pipeworx.io/cdc/mcp returns the tools in the table above plus the shared Pipeworx meta-tools — ask_pipeworx, discover_tools, search_within, remember/recall and the rest of the gateway-wide set. So the tool count you see is larger than this table: a single-pack endpoint currently lists roughly 30 shared tools alongside the pack's own. The connection's initialize response states its exact scope, and is the authoritative answer for a given day.

This is deliberate, not multiplexing by accident. The meta-tools are what let a scoped connection answer a question this pack does not cover — via ask_pipeworx, which routes across the whole catalog — without you adding a second MCP server. There is currently no way to mount a pack endpoint without them; if the extra schemas cost you more context than the routing is worth, connect to the full gateway once rather than to several pack endpoints.

Or connect to the full Pipeworx gateway to get every pack's tools listed directly, instead of just this one's:

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

Both URLs reach the same gateway and the same 1683+ data sources. The only difference is which pack's tools are listed directly; ask_pipeworx reaches all of them from either one.

No MCP client? Call it over HTTP

curl -X POST https://gateway.pipeworx.io/v1/tools/cdc_search_datasets \
  -H 'Content-Type: application/json' \
  -d '{"query":"covid cases"}'

No account needed for the first calls. Inspect any tool: GET https://gateway.pipeworx.io/v1/tools/cdc_search_datasets. Find one: POST https://gateway.pipeworx.io/v1/tools/search_packs with {"query":"..."}.

Standalone (no gateway account)

This package also runs as a local stdio MCP server — no Pipeworx account, no gateway round-trip:

{
  "mcpServers": {
    "cdc": {
      "command": "npx",
      "args": ["-y", "@pipeworx/mcp-cdc"]
    }
  }
}

Or run it directly to confirm it starts:

npx -y @pipeworx/mcp-cdc

It speaks MCP over stdin/stdout and answers initialize/tools/list/tools/call for only this pack's tools — none of the shared meta-tools the gateway connection above adds. Same source, same tools, no ask_pipeworx routing.

Using with ask_pipeworx

Instead of calling tools directly, you can ask questions in plain English — this works on the pack endpoint above as well as on the full gateway:

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