Resolve FDA application numbers and product names to regulatory metadata (CDER, CBER, CDRH).
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Inspect callable tools, capabilities, and parameters exposed to AI agents by OpenFDA Regulatory Metadata.
search_drug_labelSearch SPL label text, optionally scoped to a section
lookup_drugsfda_applicationDrugs@FDA record for an NDA/BLA/ANDA number
resolve_drug_to_applicationBrand or generic name β application number(s)
screen_for_rwe_signalsExperimental.** Sweep labels for RWE signals
lookup_device_submissionK / DEN / P / H number β device record
classify_device_product_codeProduct code β device class + medical specialty
An MCP server exposing FDA regulatory metadata (drugs, biologics, and medical devices) through the openFDA API.
Built by Black Swan Causal Labs as the identifier-resolution layer for a real-world-evidence (RWE) case roster: given an FDA application number or a product name, resolve it to authoritative regulatory metadata.
There are other openFDA MCP servers, and several are broader. This one is narrow on purpose: it is the instrument that resolved the application numbers in a specific published RWE dataset, and it exists so that dataset can name the tool that produced it.
That matters more than it might sound. Whether BLA 125123/2058 resolves to a
particular product, or DEN160026 to a particular device class, is a decision
made by a piece of software β and a different wrapper can yield a different
roster. "We used openFDA" is not a sufficient methods statement; "openfda-mcp
v0.1.0" is. If you use this in research, pin the version.
Its practical edge over a general openFDA client is the device half: resolving a CDRH submission number to a risk class takes a three-hop chain (number β product code β classification) with two non-obvious traps, both handled here.
Drugs and biologics (/drug/* β CDER, CBER)
| Tool | Purpose |
|---|---|
search_drug_label | Search SPL label text, optionally scoped to a section |
lookup_drugsfda_application | Drugs@FDA record for an NDA/BLA/ANDA number |
resolve_drug_to_application | Brand or generic name β application number(s) |
screen_for_rwe_signals | Experimental. Sweep labels for RWE signals |
Devices (/device/* β CDRH)
| Tool | Purpose |
|---|---|
lookup_device_submission | K / DEN / P / H number β device record |
classify_device_product_code | Product code β device class + medical specialty |
validate_device_application | Full chain: number β class, specialty, category |
Add to your MCP client config:
The API key is optional. Without one, openFDA allows 40 requests/min and 1,000/day, which is enough for interactive use. A free key raises it to 240/min and 120,000/day β worth having for bulk sweeps.
Both were established empirically and are not obvious from FDA's docs.
De Novo grants live in the 510(k) endpoint. DEN###### numbers are stored
in the k_number field of /device/510k. There is no De Novo endpoint, and
looking for one leads to the wrong conclusion that De Novo numbers can't be
resolved. They can.
HDE numbers are not in openFDA at all. Neither the 510(k) nor the PMA
endpoint carries H######, so no product code β and therefore no classification
β is retrievable. This server still reports device_class: "III" for them, by
regulatory inference: HDE is by definition the pathway for devices that would
otherwise require a PMA. medical_specialty stays null, because that one really
is unavailable, and device_class_source says which is which.
A genuine absence and a failed request are different things, and this package keeps them different:
None; safe to cacheOpenFDATransientError; never cache thisOpenFDARequestErrorThis is a direct response to a real defect: an earlier version swallowed every
exception and returned None, so a single read timeout on one application
number was cached as a real miss and silently blanked two fields on that record
for weeks. Cached failures are indistinguishable from real absences, which makes
them the worst kind of silent data loss.
screen_for_rwe_signalsIt is unvalidated. There is no ground-truth oracle for a discovery sweep, and below the strongest hits the results are dominated by applications whose labels use "registry" in an unrelated sense. Treat its output as candidates for human review β not as a finding, and not as a count to report. Establishing recall against a held-out set of known cases is open work.
Live tests assert against known-good fixtures (K203571 β class II Ophthalmic,
DEN160026 β class II Immunology, BLA761180 β LEO Pharma) so a change on
FDA's side surfaces as a test failure rather than as quietly wrong data.
MIT
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