About fdarecords
fdarecords is an openFDA API client for researchers and developers looking up drug labels and applications, or tracing medical device submissions and classifications. Its seven tools distinguish no-match results from transient failures and identify its experimental signal screening as unvalidated.
Key features
- 01Search drug labels and sections
- 02Look up drug application records and numbers
- 03Find device records by submission number
- 04Classify device product codes
- 05Validate device application details
- 06Screen labels for real-world evidence signals
Use cases
- 01Find indication details in drug labels
- 02Resolve application numbers from drug names
- 03Trace device submissions and regulatory classes
- 04Flag evidence signals for human review
MCP support
Exposes seven openFDA lookup tools to MCP clients for drug labels, application records, and device submissions and classifications.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
7Saved tool list · updated 1w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| limit | integer | No | Maximum number of results to return (optional). |
| query | string | Yes | Search query text. |
| section | string | No | The section for this call. |
Details
From the project READMEfdarecords
FDA records without the portal spelunking. fdarecords is a small client for the openFDA API that covers the two lookup jobs people actually repeat: finding drug information — label text, the Drugs@FDA application behind a product, the application numbers behind a name — and tracing a medical device from its submission number to its regulatory class.
Seven tools do the work. Three of them lean on findings
from the original project worth knowing up front: De Novo
(DEN) numbers are filed inside the 510(k) endpoint's
k_number field, because openFDA has no De Novo endpoint
of its own; HDE (H) numbers are not in openFDA at all, so
an H lookup answers null without pretending otherwise;
and the validation chain still reports class III for an H
number, labelled as regulatory inference rather than data.
One tool is a research aid, not an oracle:
screen_for_rwe_signals sweeps drug labels for
real-world-evidence vocabulary and returns whatever it
finds. It is experimental and unvalidated — treat its hits
as candidates for a human to review, never as findings.
Configuration
OPENFDA_API_KEY(optional) — an openFDA API key. When set it travels as theapi_keyquery parameter and buys higher rate limits. Nothing requires it; every tool works keyless.OPENFDA_BASE_URL(optional) — API base URL. Defaults tohttps://api.fda.gov.
The result contract
Every tool follows the same rules, and they are worth stating plainly because they decide what a "no" looks like:
- A query that matches nothing returns the JSON text
null. That covers an HTTP 404 and a 200 whose result list is empty. - A transient failure — a timeout, a connection error, a
429, a 5xx — is retried twice with backoff. If it still
fails, the tool raises
openfda transient failure: .... A transient failure is never reported as a miss, so anullalways means "not there", never "couldn't ask". - Any other rejected request (a different 4xx) raises
openfda request error: HTTP <status>immediately. - Bad arguments fail before any request:
<arg> must be a non-empty string, orlimit must be an integer between 1 and 100.
Single-record tools return the first matching record as JSON. The two label tools return the upstream response body exactly as it arrived.
Tools
search_drug_label— search SPL label text for aquery. Pass asection(an SPL field name such asindications_and_usage) to confine the search to that section. Optionallimit, default 10.lookup_drugsfda_application— the Drugs@FDA record for anapplication_number(NDA, BLA and ANDA numbers all work).resolve_drug_to_application— go from a brand or genericnameto the application numbers filed under it, returned as a sorted JSON array of distinct strings.screen_for_rwe_signals— the experimental sweep described above. An optionalqueryadds one more term to the fixed signal set; optionallimit, default 10.lookup_device_submission— a device record for asubmission_number. K and DEN numbers search the 510(k) endpoint; P numbers search the PMA endpoint; H numbers returnnull(not in openFDA); anything else is rejected as an unrecognized prefix.classify_device_product_code— the device class and medical specialty for aproduct_code.validate_device_application— the full chain in one call: fromsubmission_numberthrough its product code todevice_class,medical_specialtyanddevice_name, with adevice_class_sourcesaying where the class came from. H numbers short-circuit to the labelled inference result; a record with no product code comes back with"device_class": nullmerged in.
Endpoint provenance
GET /drug/label.json is the path pinned on the openFDA
API index. The remaining paths follow the same documented
pattern for their endpoint families and are labelled as
pattern-derived rather than pinned:
GET /drug/drugsfda.json— pattern-derivedGET /device/510k.json— pattern-derivedGET /device/pma.json— pattern-derivedGET /device/classification.json— pattern-derived
Three behaviours are compositions built for this client,
and are labelled as such in the code: how
resolve_drug_to_application merges its brand-name and
generic-name queries, the signal term set
screen_for_rwe_signals searches for, and the shape
validate_device_application composes from its two
records.
CLI
Each tool is a subcommand taking one JSON argument string:
npx @reneturcios/fdarecords search_drug_label '{"query":"aspirin"}'
npx @reneturcios/fdarecords search_drug_label '{"query":"chest pain","section":"indications_and_usage","limit":25}'
npx @reneturcios/fdarecords lookup_drugsfda_application '{"application_number":"NDA021457"}'
npx @reneturcios/fdarecords resolve_drug_to_application '{"name":"Tylenol"}'
npx @reneturcios/fdarecords screen_for_rwe_signals '{"query":"diabetes"}'
npx @reneturcios/fdarecords lookup_device_submission '{"submission_number":"K123456"}'
npx @reneturcios/fdarecords classify_device_product_code '{"product_code":"ABC"}'
npx @reneturcios/fdarecords validate_device_application '{"submission_number":"H123456"}'
npx @reneturcios/fdarecords --version
Output is the tool's result text (null, a record, an
array, or the upstream body). Exit codes: 0 on success,
1 on a runtime error (including a validation or upstream
failure), 2 on a usage error.
MCP server
npx -y @reneturcios/fdarecords mcp
MCP client config:
{
"mcpServers": {
"fdarecords": {
"command": "npx",
"args": ["-y", "@reneturcios/fdarecords", "mcp"]
}
}
}
Docker
docker run -i ghcr.io/cloudcorprecords/fdarecords
docker run --rm ghcr.io/cloudcorprecords/fdarecords lookup_device_submission '{"submission_number":"DEN200001"}'
Development
npm install
npm run build # tsc -> dist/
npm test # tsx --test test/*.test.ts (fake fetch only, no network)
npm run dev # run the CLI from source
License
MIT — Copyright (c) 2026 Rene Turcios
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.