Mirobody
Lab results to LOINC codes and UCUM units, symptoms and diagnoses to ICPC-3. Offline, no API key.
作者提供的说明(英文原文)
openFDA identifier resolution: drug labels and applications, device submissions, classification.
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。
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。
选择你使用的 AI 应用,然后复制设置。
你需要
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。
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。
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
注册名称已通过 GitHub 账户 CloudCorpRecords 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
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。
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。
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)。
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。
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。
同一分类中有:Mirobody, FHIR MCP Server, Google Health MCP
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
Lab results to LOINC codes and UCUM units, symptoms and diagnoses to ICPC-3. Offline, no API key.
MCP server providing seamless access to FHIR APIs for AI tools and healthcare applications
Privacy-first unofficial Google Health API v4 MCP server for health, sleep, activity, HR agents
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。
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.
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.Every tool follows the same rules, and they are worth stating plainly because they decide what a "no" looks like:
null. That covers an HTTP 404 and a 200 whose result list is empty.openfda transient failure: .... A transient failure is never reported as a miss, so a null always means "not there", never "couldn't ask".openfda request error: HTTP immediately. 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.
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.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-derivedThree 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.
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.
npx -y @reneturcios/fdarecords mcp
MCP client config:
{
"mcpServers": { "fdarecords": { "command": "npx", "args": ["-y", "@reneturcios/fdarecords", "mcp"] } } }
docker run -i ghcr.io/cloudcorprecords/fdarecords
docker run --rm ghcr.io/cloudcorprecords/fdarecords lookup_device_submission '{"submission_number":"DEN200001"}'
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
MIT — Copyright (c) 2026 Rene Turcios