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Cdc Health MCP Server

answering

Cdc Health MCP Server is answering right now. Last checked 14 min ago. 262 installs a week from npm. It exposes 4 tools. Last commit 16 Sep 2026.

Search and query CDC public health data — mortality, vaccinations, surveillance, behavioral risk.

Installs per day peak 176 · avg 37 · +435% w/w
a month agotoday
Uptime history 47 days of history · worst day 0%
47 days agonow
100.0%
Uptime 24h
91 of 91 checks
4
Tools
read from the server
380 ms
Response time
average over 24h
262
Installs / week
npm and PyPI

What changed 18

Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 9 August 2026. No other catalogue keeps this.

16 Sep a tool changed version
22 Aug 4 tools changed the parameters they ask for cdc_discover_datasets, cdc_get_dataset_schema, cdc_query_dataset and 1 more
22 Aug a tool changed version
18 Aug 3 tools changed the parameters they ask for cdc_get_dataset_schema, cdc_query_dataset, cdc_query_wonder
18 Aug 2 tool descriptions were rewritten cdc_get_dataset_schema, cdc_query_wonder
18 Aug a tool changed version
9 Aug 4 tools changed the parameters they ask for cdc_discover_datasets, cdc_get_dataset_schema, cdc_query_dataset and 1 more
9 Aug 2 tool descriptions were rewritten cdc_discover_datasets, cdc_query_wonder

Nothing serious here today

Today is the operative word: we check Cdc Health MCP Server every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.

Three servers free · no card

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 14 min ago.

run in your terminal
claude mcp add cdc-health-mcp-server --transport http https://cdc.caseyjhand.com/mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "cdc-health-mcp-server": {
      "url": "https://cdc.caseyjhand.com/mcp"
    }
  }
}
~/.codex/config.toml
[mcp_servers.cdc-health-mcp-server]
url = "https://cdc.caseyjhand.com/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "cdc-health-mcp-server": {
      "url": "https://cdc.caseyjhand.com/mcp"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "cdc-health-mcp-server": {
      "url": "https://cdc.caseyjhand.com/mcp"
    }
  }
}

This one needs environment variables set before it will start: CDC_APP_TOKEN (Socrata app token for higher rate limits.), MCP_HTTP_HOST (The hostname for the HTTP server.), MCP_HTTP_PORT (The port to run the HTTP server on.), MCP_HTTP_ENDPOINT_PATH (The endpoint path for the MCP server.), MCP_AUTH_MODE (Authentication mode to use: 'none', 'jwt', or 'oauth'.), MCP_LOG_LEVEL (Sets the minimum log level for output (e.g., 'debug', 'info', 'warn').). The author declared them in the registry entry; get the values from the project itself.

Available tools 4

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

cdc
cdc_discover_datasets
Search the CDC dataset catalog by keyword, category, or tag. Returns IDs, names, truncated descriptions, asset types, column counts, and update timestamps. The catalog also holds charts, maps, stories, files, and links; an entry whose columnCount is 0 is one of those and yields no data from the other tools. Use cdc_get_dataset_schema for the full column list of a chosen dataset.
cdc_get_dataset_schema
Fetch the column schema for a CDC dataset — names, data types, descriptions, row count, and last-updated timestamp. Returns the first 100 columns by default; wide datasets continue via column_offset. Get dataset IDs from cdc_discover_datasets.
cdc_query_dataset
Execute a SoQL query against any CDC dataset. Supports filtering, aggregation, sorting, full-text search, and field selection. Use cdc_discover_datasets to find dataset IDs and cdc_get_dataset_schema to inspect columns before querying.
cdc_query_wonder
Query CDC WONDER for national US mortality statistics — deaths, population, and crude/age-adjusted death rates — across its five mortality databases, selected with the database input: final underlying-cause data for 1999–2020 (the default) or 2018–2024, provisional data running from 2018 through the current year, and two multiple-cause databases covering the same two eras. Break results out by year, age group, sex, and/or race, and filter by ICD-10 cause of death, sex, age group, or year range; on a multiple-cause database, mcd_icd10 additionally matches a cause listed anywhere on the death certificate rather than only the one certified as underlying. Each database holds a different span of years (1999–2026 across all of them) and a request whose year_range falls outside the selected one's span is rejected with that span named. WONDER is a separate CDC system from the Socrata datasets the other cdc_* tools query. Data is national only — sub-national (state/county) breakdowns are not available through the API (CDC vital-statistics policy). Cause of death is a filter, not a grouping. Some measure cells come back as a CDC status token rather than a number — "Suppressed" (withheld for confidentiality), "Unreliable" (a rate from fewer than 20 deaths), or "Not Applicable" (no population denominator); those cells read null in rows and each one is listed in cellNotes with its token. CDC also drops whole rows before sending the table — strata with zero deaths, and strata whose death count is suppressed — so a stratum can be missing from rows entirely; messages carries CDC's statement whenever that happened. The whole table comes back by default; a broad grouping can run past a thousand rows, so set limit to take it a page at a time and follow the nextOffset the response reports. Paging shapes the response only — WONDER is asked once either way, and the figures, caveats and hidden-row notices are the same on every page. CDC rejects requests made less than 15 seconds apart across all five databases, so consecutive calls are spaced automatically and a follow-up call may wait about 16 seconds before it runs.

Endpoints

URLTransportStateLatencyChecked
https://cdc.caseyjhand.com/mcp streamable-http answering 399 ms 14 min ago

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Cdc Health MCP Server — questions

Answers built from our own checks of this server.

What can Cdc Health MCP Server do?
It exposes 4 tools, read directly from the server on our last check. Among them: cdc_discover_datasets, cdc_get_dataset_schema, cdc_query_dataset, cdc_query_wonder. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
Is Cdc Health MCP Server working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 380 ms. The bar chart above shows every period we have measured.
How do I connect Cdc Health MCP Server?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does Cdc Health MCP Server need an API key?
No. Cdc Health MCP Server completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 4 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is Cdc Health MCP Server?
It answers our handshake in 380 ms on average, which is faster than 40% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.
How many people use Cdc Health MCP Server?
The npm package @cyanheads/cdc-health-mcp-server was installed 262 times in the last week. Week over week that is +435%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.
Is Cdc Health MCP Server open source?
Yes — it is published under the Apache-2.0 licence, written in TypeScript, 5 stars on GitHub and 3 open issues. The source link is on this page, so you can read exactly what it does with your data before you connect it.