vaers
MCP serverEverything elseVAERS (Vaccine Adverse Event Reporting System) — report counts by vaccine,
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use vaers
From the project's README
As published by pipeworx-io/mcp-vaers in README.md.
VAERS (Vaccine Adverse Event Reporting System) report counts — by vaccine, manufacturer, symptom, year and severity. Fleet #1294.
Part of Pipeworx — an MCP gateway connecting AI agents to 1558+ live data sources.
A VAERS report is not a confirmed adverse event — read this first
Anyone can file a VAERS report — a patient, a parent, a clinician, a manufacturer — and VAERS does not verify what's in it. A rise in report counts for a vaccine can reflect more doses given, more media attention, or a reporting-requirement change just as easily as a real safety signal. CDC and FDA say this about their own data:
The number of reports alone cannot be interpreted as evidence of a causal association between a vaccine and an adverse event, or as evidence about the existence, severity, frequency, or rates of problems associated with vaccines. Reports may include incomplete, inaccurate, coincidental, and unverified information. — https://wonder.cdc.gov/wonder/help/vaers.html
Every tool response below carries that disclaimer and a literal
is_causal: false field, so a model reading the payload cannot round a report
count up into a causal claim. No tool here returns a single report's free
text (SYMPTOM_TEXT, HISTORY, LAB_DATA, OTHER_MEDS, CUR_ILL,
ALLERGIES are not even stored — see the migration comment) — everything is
a count, by design.
Tools
| Tool | Answers |
|---|---|
vaers_events_by_vaccine | Report counts + severity breakdown by vaccine (and optionally manufacturer), for a year range. Omit vaccine to browse the top vaccines by report volume — this doubles as vax_type-code discovery. |
vaers_events_by_symptom | Report-mention counts by symptom (MedDRA preferred term), optionally narrowed to one vaccine/year range. Omit symptom to see the most-reported symptoms. |
vaers_coverage | Total unique reports, year range, distinct vaccine/manufacturer counts, when the seed was last loaded, and the top 5 vaccines by volume. |
Counting convention — read before comparing numbers across tools
A report that names more than one vaccine is counted once per vaccine —
the same convention CDC WONDER itself uses for VAERS. So summing
report_count across every vaccine for a year can exceed that year's
unique report total (vaers_coverage.total_unique_reports). Symptom
counts are mentions: a report naming several symptoms and/or several
vaccines contributes to each combination.
Auth
None — no key, no account. This pack answers from pre-aggregated report counts built from the seed described below.
Data source and how it got here
VAERS, co-run by CDC and FDA — public data files at https://vaers.hhs.gov/data/datasets.html. US federal public-domain data.
Every automated surface CDC exposes for VAERS is closed to a script:
- The bulk-download page is CAPTCHA-gated (image word-verification).
- CDC WONDER's own XML API documents VAERS (database
D8) as a live dataset but the endpoint returnsHTTP 500with no error message for every request shape tried — recognized but not enabled, undocumented. data.cdc.gov's two VAERS listings arehrefpointers back to WONDER, not queryable Socrata datasets.
Full write-up: docs/vaers-access-finding.md.
So Bruce's ruling (task #1294, 2026-09-07) is seed-plus-manual-refresh:
he downloads AllVAERSDataCSVS.zip (the single archive covering every year,
1990-2026, plus non-domestic reports) by hand from the datasets page above,
and this pack's loader ingests it. He explicitly did not authorize the
outward-facing option (emailing CDC to ask for the API to be enabled) — that
still needs his own OK if it's ever pursued.
Storage — why aggregates, not raw rows
The seed is 2.8M report rows / 3.4M vaccine rows / 3.77M symptom rows (2.75GB
uncompressed CSV, 589MB zip). Postgres here is small and has crashed on an
unbatched load before (docs/medical-data-ingest-plan.md §3), and this
pack's tools only ever answer count questions — never a raw-row dump — so the
loader (scripts/ingest-vaers.mjs) aggregates entirely in memory and writes
only the aggregates, in committed batches:
| Table | Grain | Measured rows (1990-2026 + non-domestic seed) |
|---|---|---|
vaers_yearly_totals | year | 37 |
vaers_severity_by_vaccine | year × vax_type × manufacturer | 4,975 |
vaers_symptom_counts | year × vax_type × symptom | 961,457 |
Total Postgres footprint: tens of MB, not gigabytes. Three RPCs
(vaers_vaccine_stats, vaers_symptom_stats, vaers_coverage_stats, see
supabase/migrations/165_vaers_aggregates.sql) do the filtering/summing in
SQL since the tables are small enough that a plain GROUP BY is fast.
Compression note, since this class of bug has bitten a sibling ingest
before (NCHS natality was Deflate64, unreadable by Node's zlib): checked
first — every entry in AllVAERSDataCSVS.zip is method 8 (plain Deflate),
which node:zlib.inflateRawSync reads natively. No Deflate64 trap here.
Refreshing (manual, by design)
VAERS updates weekly. There is no automated path around the CAPTCHA, so refresh is:
- A human downloads a fresh
AllVAERSDataCSVS.zipfrom https://vaers.hhs.gov/data/datasets.html. node scripts/ingest-vaers.mjs /path/to/AllVAERSDataCSVS.zip
The loader is idempotent (ON CONFLICT ... DO UPDATE) and re-runnable — a
rerun with the same or a newer file simply updates the aggregates in place.
It refuses to load a result that looks truncated (fewer than 20 years, 1,000
severity keys, or 100,000 symptom keys) rather than quietly shrinking the
dataset.
Proposed cadence: weekly, matching VAERS' own release rhythm — one
re-download + rerun per week keeps vaers_coverage.data_last_loaded inside
a week of the live data. This is a recurring cost of Bruce's time by design
(his ruling); if an automated path ever opens up (CDC enabling the WONDER
API for D8, or a future scrape-friendly surface), this is the loader to
replace, not the schema.
Two write paths, chosen automatically
ingest-vaers.mjs looks for the platform's database credentials in .env
first (fast REST batched upsert). If they aren't available in the
environment it's run from, it falls back to writing chunked, idempotent SQL
files to /tmp/vaers-sql/ and printing the supabase db query --file ... --linked commands to apply them — the same Management-API path used to
apply supabase/migrations/165_vaers_aggregates.sql. Either path produces
the same tables.
What this does not cover
- Individual report narratives (
SYMPTOM_TEXT,HISTORY, etc.) — not stored, not returned, by design (see above). - Anything past the loaded seed's vintage — check
vaers_coveragebefore relying on recency. - FAERS (drug adverse events) — that's
openfda. VAERS is vaccines only.
Quick Start
Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):
{
"mcpServers": {
"vaers": {
"url": "https://gateway.pipeworx.io/vaers/mcp"
}
}
}
What this endpoint actually serves
tools/list at https://gateway.pipeworx.io/vaers/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 1558+ data sources. The
only difference is which pack's tools are listed directly; ask_pipeworx
reaches all of them from either one.
Standalone (no gateway account)
This package also runs as a local stdio MCP server — no Pipeworx account, no gateway round-trip:
{
"mcpServers": {
"vaers": {
"command": "npx",
"args": ["-y", "@pipeworx/mcp-vaers"]
}
}
}
Or run it directly to confirm it starts:
npx -y @pipeworx/mcp-vaers
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 Vaers data" })
The gateway picks the right tool and fills the arguments automatically.
More
License
MIT
Advanced
- Delivery
- vaers MCP server → your ahel gateway (mcp.ahel.ai) → every connected AI client.
- Catalog kind
- mcp-server
- Gateway key
io-github-pipeworx-io-vaers- Source
- github.com/pipeworx-io/mcp-vaers
- Hosted endpoint
https://gateway.pipeworx.io/vaers/mcp