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)
MCP Server for evipedia.ai — evidence-based reviews of health & longevity interventions
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": {
"evipedia": {
"command": "npx",
"args": [
"-y",
"evipedia-mcp"
]
}
}
}在终端中运行这条命令
claude mcp add evipedia -- npx -y evipedia-mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"evipedia": {
"command": "npx",
"args": [
"-y",
"evipedia-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": {
"evipedia": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"evipedia-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 GitHub 账户 forever-healthy 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(0.1.30)于2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 Node.js。
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:↓ 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
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。
_2026-Forever_Healthy-573D7D.svg)
A small Model Context Protocol server that lets AI agents query evipedia.ai — our continuously-updated encyclopedia of evidence reviews on health & longevity interventions — and suggest new interventions for review.
search_reviews(query) → matching reviews (name/synonym/keyword/category), each with its URL and conclusionlist_reviews() → the full catalogue as {topic, slug} pairs (canonical topic + the slug you pass to get_review/get_conclusion)list_updates(days?) → the change feed, newest first: {title, slug, status, date} per recently published (new) or revised (updated) review. With no arguments it returns the last 7 days, capped at 100 entries; pass days for a wider window (e.g. days: 30)get_conclusion(slug|url) → just the review's plain-text conclusionget_review(slug|url) → the full review as raw Markdownget_metadata(slug|url) → structured medical metadata as JSON — review dates (datePublished/dateModified/lastReviewed, a freshness signal not in the Markdown), the typed about entity with alternate names, and an ordered citation list with PubMed PMIDsThe read tools accept either a bare slug (e.g. rapamycin) or a full evipedia.ai URL (e.g. https://evipedia.ai/rapamycin) — the URL's last path segment is the slug, so a search result's URL can be passed straight through.
suggest_review(intervention, goal?, references?, email?) → submit a new review for an intervention to evipedia's public suggestion form (the same one at evipedia.ai/suggest)get_version() → the running server's package name and versionThe server is published to npm as [`evipedia-mcp`](https://www.npmjs.com/package/evipedia-mcp) and runs over stdio via npx — no global install needed. It's also listed in the official MCP Registry as `io.github.forever-healthy/evipedia-mcp`, so MCP-aware clients can discover and install it automatically.
Client config: Local MCP (Requires Node.js ≥ 18)
{
"mcpServers": { "evipedia": { "command": "npx", "args": ["-y", "evipedia-mcp"] } } }
For environments where a local install is not possible or desired, we also provide a hosted MCP server at https://mcp.evipedia.ai/ that can be used over HTTP.
Client config: Remote MCP via HTTP
{
"mcpServers": { "evipedia": { "type": "http", "url": "https://mcp.evipedia.ai/mcp" } } }
.mcp.json (or run claude mcp add).claude_desktop_config.json.You can use the bundled `/demo` skill to smoke-test the respective connection.
It walks through the read tools (get_version, search_reviews, list_reviews, list_updates, get_review, get_conclusion, get_metadata) against live evipedia.ai data.
The server is a thin client that only uses evipedia.ai's public endpoints. It does not depend on the evipedia content repo — the public surfaces are the API by design.
https://evipedia.ai with a small in-process cache (both JSON indexes are tiny)suggest_review, which POSTs to evipedia's public suggestion form (Formspree)Base URL: https://evipedia.ai
| Endpoint | Description |
|---|---|
GET /reviews.json | Full catalogue: canonical_name, alternate_names[], permalink, permalink_md, permalink_meta, category, creation_date, dateModified, lastReviewed, er_conclusion |
GET /search.json | Search index: short_topic, alternate_names, ep_keywords, ep_category, url |
GET /updates.json | Change feed, newest first: title, permalink, status (new/updated), date |
GET /{permalink}.md | Complete review as raw Markdown (frontmatter + full body) |
GET /{permalink}.meta.json | Flattened medical metadata: slug, topic, url, datePublished/dateModified/lastReviewed, about (type/name/alternateName), ordered citation[] (name, url, pmid?) |
GET /llms.txt | Agent/human signpost — includes the stable section anchor list |
GET /sitemap.xml | Canonical review URLs |
GET /feed.xml | RSS feed of latest updates |