@pipeworx/vaers

Connect: https://gateway.pipeworx.io/vaers/mcp · Install: one-click buttons

Tools: 3

VAERS (Vaccine Adverse Event Reporting System) report counts — by vaccine, manufacturer, symptom, year and severity. Fleet #1294.

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

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 returns HTTP 500 with no error message for every request shape tried — recognized but not enabled, undocumented.
• data.cdc.gov’s two VAERS listings are href pointers 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:

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:

1. A human downloads a fresh AllVAERSDataCSVS.zip from https://vaers.hhs.gov/data/datasets.html.
2. 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_coverage before relying on recency.
• FAERS (drug adverse events) — that’s openfda. VAERS is vaccines only.

Tools

• vaers_events_by_vaccine — VAERS report counts and severity breakdown (died / life-threatening / hospitalized / disabled / ER visit) by vaccine, for the requested year range. Pass vaccine as the VAERS vax_type code (e.g. “COV
• vaers_events_by_symptom — VAERS report counts by symptom (MedDRA preferred term), optionally filtered to one vaccine and/or year range. Pass symptom as a substring (e.g. “headache”, “anaphyla”, “myocarditis”) to count how of
• vaers_coverage — What this VAERS pack currently holds: total unique reports, the year range covered, how many distinct vaccine types and manufacturers, and when the seed was last (re)loaded — refresh is a manual re-do