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PopNx MCPMCP servers for people who use AI · explained in plain words

Fdarecords

by CloudCorpRecordsversion 0.1.0i★ –iRuns on your computer
Registry nameio.github.CloudCorpRecords/fdarecords

Install

Overview

Description from the maker (original English)

openFDA identifier resolution: drug labels and applications, device submissions, classification.

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: Clinics & health

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

  • npmNode.js installed (for the npx 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": {
    "fdarecords": {
      "command": "npx",
      "args": [
        "-y",
        "@reneturcios/fdarecords",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add fdarecords -- npx -y @reneturcios/fdarecords mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "fdarecords": {
      "command": "npx",
      "args": [
        "-y",
        "@reneturcios/fdarecords",
        "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": {
    "fdarecords": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@reneturcios/fdarecords",
        "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 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account CloudCorpRecords, which owns the repo

  • … 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 Clinics & healthi

  • More stars than 0% of the other 866 servers in this category
  • Published to the registry more recently than 88% of the other 866 servers in this category
  • Basic checks equal to or better than 100% of the other 866 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 Fdarecords 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 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js, Docker on your computer.

What can I use instead?

In the same category: Mirobody, FHIR MCP Server, Google Health MCP

Alternatives

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

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Lab results to LOINC codes and UCUM units, symptoms and diagnoses to ICPC-3. Offline, no API key.

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Runs on your computer★ 79MITUpdated 4 months ago
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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.

fdarecords

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 the api_key query parameter and buys higher rate limits. Nothing requires it; every tool works keyless.
  • OPENFDA_BASE_URL (optional) — API base URL. Defaults to https://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 a null always means "not there", never "couldn't ask".
  • Any other rejected request (a different 4xx) raises openfda request error: HTTP immediately.
  • Bad arguments fail before any request: must be a non-empty string, or limit 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 a query. Pass a section (an SPL field name such as indications_and_usage) to confine the search to that section. Optional limit, default 10.
  • lookup_drugsfda_application — the Drugs@FDA record for an application_number (NDA, BLA and ANDA numbers all work).
  • resolve_drug_to_application — go from a brand or generic name to 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 optional query adds one more term to the fixed signal set; optional limit, default 10.
  • lookup_device_submission — a device record for a submission_number. K and DEN numbers search the 510(k) endpoint; P numbers search the PMA endpoint; H numbers return null (not in openFDA); anything else is rejected as an unrecognized prefix.
  • classify_device_product_code — the device class and medical specialty for a product_code.
  • validate_device_application — the full chain in one call: from submission_number through its product code to device_class, medical_specialty and device_name, with a device_class_source saying 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": null merged 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-derived
  • GET /device/510k.json — pattern-derived
  • GET /device/pma.json — pattern-derived
  • GET /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

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