Tolca
Web search + clean page text with sha256 proof, and company, sanctions and licence checks (x402)
作者提供的说明(英文原文)
Resolve FDA application numbers and product names to regulatory metadata (CDER, CBER, CDRH).
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": {
"openfda": {
"command": "uvx",
"args": [
"openfda-mcp"
]
}
}
}在终端中运行这条命令
claude mcp add openfda -- uvx openfda-mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"openfda": {
"command": "uvx",
"args": [
"openfda-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": {
"openfda": {
"type": "stdio",
"command": "uvx",
"args": [
"openfda-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9日
注册名称已通过域名 blackswancausallabs.com 验证(注册中心会核实域名所有权)
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个月前进入注册中心。
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 Python (uv)。
同一分类中有:Tolca, Tilt Base, Korea Data 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:↓ 每周下载量i★ 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
Web search + clean page text with sha256 proof, and company, sanctions and licence checks (x402)
Tilt Legal's managed legal skills and your organisation's custom skills, for your AI agent.
Korean public data: corporate filings, stock prices, apartments, statutes, economic statistics
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。
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 — 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.
Drugs and biologics (/drug/* — 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 → application number(s) |
screen_for_rwe_signals | Experimental. Sweep labels for RWE signals |
Devices (/device/* — CDRH)
| Tool | Purpose |
|---|---|
lookup_device_submission | K / DEN / P / H number → device record |
classify_device_product_code | Product code → device class + medical specialty |
validate_device_application | Full chain: number → class, specialty, category |
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.
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.
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 — not as a finding, and not as a count to report. Establishing recall against a held-out set of known cases is open work.
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.
MIT