原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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Fdarecords

作者:CloudCorpRecords版本 0.1.0i★ –i在你的电脑上运行
注册名称io.github.CloudCorpRecords/fdarecords

安装

概览

作者提供的说明(英文原文)

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

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 诊所与健康

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "fdarecords": {
      "command": "npx",
      "args": [
        "-y",
        "@reneturcios/fdarecords",
        "mcp"
      ]
    }
  }
}

在终端中运行这条命令

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

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "fdarecords": {
      "command": "npx",
      "args": [
        "-y",
        "@reneturcios/fdarecords",
        "mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "fdarecords": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@reneturcios/fdarecords",
        "mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 CloudCorpRecords 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“诊所与健康”中的其他服务器比较i

  • 星标数多于此分类中其他 860 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 860 个服务器的 89% 更新
  • 基础检查结果等于或优于此分类中其他 860 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Fdarecords 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.1.0)于3天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js, Docker。

有什么可以替代它?

同一分类中有:Mirobody, FHIR MCP Server, Google Health MCP

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Mirobody

作者:thetahealth

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

在你的电脑上运行★ 1,408Apache-2.05天前更新
安装

FHIR MCP Server

作者:wso2

MCP server providing seamless access to FHIR APIs for AI tools and healthcare applications

在你的电脑上运行★ 137Apache-2.08天前更新
安装

Google Health MCP

作者:davidmosiah

Privacy-first unofficial Google Health API v4 MCP server for health, sleep, activity, HR agents

在你的电脑上运行★ 79MIT4个月前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

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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