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)
Canine genomics for agents: breed allele frequencies, AI pathogenicity + OMIA clinical disease layer
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 …”。
适用于网页版、桌面版和手机版 Claude:
https://mcp.sniff.world/mcp/在终端中运行这条命令
claude mcp add --transport http sniff https://mcp.sniff.world/mcp/粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"sniff": {
"url": "https://mcp.sniff.world/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": {
"sniff": {
"type": "http",
"url": "https://mcp.sniff.world/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。
ChatGPT 只能连接互联网上的服务器:
https://mcp.sniff.world/mcp/菜单名称可能因套餐和版本不同而略有差异。
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。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
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 sniff.world 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
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
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。
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(1.1.0)于4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。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
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。
The reference layer for dog DNA. A live, open API + MCP server over the Sniff Atlas — breed-stratified allele frequencies for 9,667,790 variants genome-wide across 188 dog breeds (CanFam4), with SnpEff annotation, Pangolin splice values, Zoonomia phyloP conservation, and a variant ⇄ gene ⇄ breed ⇄ disease knowledge graph. It assigns no pathogenicity to any variant. Every response carries its own citation + provenance.
Building anything with dogs, breeds, or canine health? This is the data layer. No key, no signup — point your agent or app at it and go.
https://mcp.sniff.world/mcp/ (Streamable HTTP; the current tool list is served at /v1/metadata) — including `ask`, a grounded canine-genetics Q&A that answers only from cited data or honestly abstains (no hallucinated dog-health advice), and `disease_bridge` (inherited-disease atoms with ACMG-style pathogenicity grades + the dog⇄human homolog)https://api.sniff.world/ (OpenAPI docs · llms.txt)The hosted server is open and needs no auth. Pick your tool:
Claude Code
claude mcp add --transport http sniff https://mcp.sniff.world/mcp/
Cursor / Windsurf / VS Code — add to your MCP config (.cursor/mcp.json, mcp.json, etc.):
{
"mcpServers": { "sniff": { "url": "https://mcp.sniff.world/mcp/" } } }
Claude Desktop or any stdio-only client (uses the hosted server via a local bridge):
{
"mcpServers": { "sniff": { "command": "npx", "args": ["-y", "sniff-mcp"] } } }
That's it. Ask your agent: *"What's the frequency of CPT2 5:56189113 across breeds?"* or *"Find HIGH-impact variants in DLA genes."*
No SDK needed — it's plain HTTP/JSON.
curl https://api.sniff.world/v1/variant/5:56189113
{
"variant_id": "5:56189113", "ref": "A", "alt": "G", "global_af": 0.0185, "popmax_af": 0.591, "popmax_breed": "akita", "consequence": "missense_variant", "impact": "MODERATE", "gene": "CPT2", "phylop_241way": 6.36, "provenance": { "dataset_doi": "10.5281/zenodo.20566358", "predicted_disease_relevance": "UNPROVEN", "...": "..." } }
// JavaScript / TypeScript
const r = await fetch("https://api.sniff.world/v1/variant/5:56189113/context?breed=akita"); const ctx = await r.json(); // frequency + annotations + gene + cross-breed + provenance
| Endpoint | What it returns |
|---|---|
GET /v1/variant/{pos} | single variant: AF, popmax, consequence, gene, Pangolin, phyloP |
GET /v1/variant/{pos}/context | the joined query — everything about a variant in one call |
GET /v1/breed/{breed} | breed profile (top variants, geometry, nearest breeds) |
GET /v1/breed/{breed}/nearest | genetically nearest breeds (PCA distance) |
GET /v1/gene/{symbol} | variants in a gene, ranked by impact |
GET /v1/semantic?q= | natural-language search ("ancient arctic sled dogs") |
GET /v1/search | filtered discovery across all 9.67M variants |
GET /v1/metadata | release, DOI, counts, scope banner |
Positions are CanFam4 chrom:pos (e.g. 5:56189113). Full schema: https://api.sniff.world/openapi.json.
uvx sniff-mcp # run the MCP server locally (needs the release data on disk)
pip install sniff-mcp # or install into your env
See [`ARCHITECTURE.md`](ARCHITECTURE.md) and [`Dockerfile`](Dockerfile). The hosted endpoint is the easy path; self-hosting is for air-gapped or high-volume use.
Built from CanVAS (14,478 dogs, Beagle-imputed, MAF≥1%) plus projected community cohorts. Annotations are not classifications: every response is flagged predicted_disease_relevance: "UNPROVEN", and Pangolin values are a third-party model's output, not validated in dogs. This is a research and discovery resource, not a clinical diagnostic. The scope (common + low-frequency variants, MAF≥1%) and the UNPROVEN caveat ride in every response's provenance block, so anything an agent quotes stays honest and self-citing.
Gehring, M. (2026). *Sniff Atlas.* Zenodo. https://doi.org/10.5281/zenodo.20566358 (CC-BY-4.0)
@dataset{sniff_atlas_2026,
author = {Gehring, Matt}, title = {Sniff Atlas}, year = {2026}, publisher = {Zenodo}, doi = {10.5281/zenodo.20566358}, url = {https://sniff.world} }
Code MIT · Data CC-BY-4.0 · world.sniff/sniff-mcp · https://sniff.world