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openFDA Regulatory Metadata

by Black-Swan-Causal-Labsversion 0.1.0i★ –iRuns on your computer
Registry namecom.blackswancausallabs/openfda-mcp

Install

Overview

Description from the maker (original English)

Resolve FDA application numbers and product names to regulatory metadata (CDER, CBER, CDRH).

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Law & government data

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "openfda": {
      "command": "uvx",
      "args": [
        "openfda-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add openfda -- uvx openfda-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "openfda": {
      "command": "uvx",
      "args": [
        "openfda-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "openfda": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "openfda-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 9, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified against the domain blackswancausallabs.com (the registry checks domain ownership)

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Law & government datai

  • More stars than 0% of the other 1767 servers in this category
  • Published to the registry more recently than 22% of the other 1767 servers in this category
  • Basic checks equal to or better than 100% of the other 1767 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is openFDA Regulatory Metadata safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.0) reached the registry 3 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Korea Data MCP, CaseNode Case Law API, Good-neighbor passport: agent traffic governor

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Korea Data MCP

Korean public data: corporate filings, stock prices, apartments, statutes, economic statistics

by YoungsoonLeeVery newUpdated today

Runs on your computer

CaseNode Case Law API

UK case law: 290k+ judgments, 2.5M citation links, citation validation. Free key at casenode.ai

by LuptonMEarlyUpdated today

Runs in the cloud

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

openFDA MCP

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.

Why this exists

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 — 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 → product code → classification) with two non-obvious traps, both handled here.

Tools

Drugs and biologics (/drug/* — CDER, CBER)

ToolPurpose
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 → application number(s)
screen_for_rwe_signalsExperimental. Sweep labels for RWE signals

Devices (/device/* — CDRH)

ToolPurpose
lookup_device_submissionK / DEN / P / H number → device record
classify_device_product_codeProduct code → device class + medical specialty
validate_device_applicationFull chain: number → class, specialty, category

Install

pip install openfda-mcp

Add to your MCP client config:

{

"mcpServers": { "openfda": { "command": "openfda-mcp", "env": { "OPENFDA_API_KEY": "${OPENFDA_API_KEY:-}" } } } }

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 — worth having for bulk sweeps.

Two findings worth knowing

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 — and therefore no classification — 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.

Transient failures are never silent

A genuine absence and a failed request are different things, and this package keeps them different:

  • not found (HTTP 404, or 200 with no results) → returns None; safe to cache
  • transient failure (timeout, connection error, 429, 5xx) → retried with backoff, then raises OpenFDATransientError; never cache this
  • rejected request (other 4xx) → raises OpenFDARequestError

This 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.

On screen_for_rwe_signals

It 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 — not as a finding, and not as a count to report. Establishing recall against a held-out set of known cases is open work.

Development

pip install -e ".[dev]"

pytest # unit tests, offline pytest -m live # live checks against api.fda.gov

Live tests assert against known-good fixtures (K203571 → class II Ophthalmic, DEN160026 → class II Immunology, BLA761180 → LEO Pharma) so a change on FDA's side surfaces as a test failure rather than as quietly wrong data.

License

MIT

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