
Meddata
io.github.anthesiallc由 GitHub 帳號 anthesiallc 發布v0.2.1更新於 Oct 24, 2026
Drug & supplement lookup and interaction checks from free U.S. government health data.
概覽
讓助理查詢美國藥品與補充品資料,並檢查一組藥品和補充品之間的交互作用。
- 可以做什麼
- 把 MedData REST API 包裝成 MCP 工具。工具包含依品牌或學名搜尋藥品的 search_drugs、依 RxCUI 取得藥品詳細資料的 get_drug、依 NDC 代碼查詢的 get_drug_by_ndc、搜尋補充品的 search_supplements、取得補充品說明資料的 get_supplement、檢查 2 到 10 項混合清單交互作用的 check_interactions、提供逐對評估及來源、服用時間與食物條件的 assess_routine,以及查詢計費週期用量的 get_usage。assess_routine 會區分有發現、已查來源但無發現、無來源涵蓋與未能解析四種情況。
- 適用情境
- 適合需要以對話方式查詢藥品或補充品資訊,或需要附來源依據的交互作用檢查的情境。assess_routine 適合結果需要解釋或據以行動的情況;check_interactions 適合只需快速列出結果的情況。
- 執行需求
- 需要本機 Python 執行環境(PyPI 套件 meddata-mcp,可用 uvx 或 pip 執行),並在 MEDDATA_API_KEY 環境變數中提供 MedData API 金鑰;可申請免費金鑰,每月 250 次呼叫。另有選用的 MEDDATA_BASE_URL 與 MEDDATA_TIMEOUT。由於與 MedData API 應用程式有相依性衝突,應安裝在獨立環境。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Meddata,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
MedData MCP Server
mcp-name: io.github.anthesiallc/meddata
A Model Context Protocol server that exposes the MedData API as tools, so any MCP client (Claude Desktop, Cursor, ChatGPT connectors, or an agent framework) can look up drug and supplement data and check interactions conversationally.
It's a thin wrapper: each tool maps to one MedData REST endpoint. All the data work happens in the API.
Tools
check_interactions vs assess_routine
check_interactions returns a flat list of interactions. assess_routine
returns the reasoning: what each submitted name resolved to, what was consulted
for every pair, and the document behind each finding. Reach for it when the
answer will be explained or acted on rather than just displayed.
The distinction that matters most is in pairs_checked[].status:
not_covered and no_finding_in_sources are different answers, and a flat
empty list cannot tell them apart.
assess_routine also takes class_matching (default off). With it on, a drug
matches the therapeutic classes a supplement record names, not only the drug
names it lists; those findings carry basis.level: "class" and name the class,
so an inferred match stays distinguishable from an explicit one. Findings also carry basis.level
(formulation / ingredient / class) saying how closely the source matches
what was submitted, three-state timing and food conditions where silence is
not_documented rather than "no effect", and references[] with the document
version and the verbatim passage.
Get an API key
Free tier is 250 calls/month, no credit card:
The key comes back in the api_key field of the response.
Install and run
The easiest way is with uv (no manual venv needed):
Or install with pip into its own environment:
Note: install into a dedicated environment. The
mcpSDK requires a newerstarlettethan the MedData API app pins, so the two will conflict if installed together.
Environment variables:
MEDDATA_API_KEY(required) — your MedData API key.MEDDATA_BASE_URL(optional) — defaults tohttps://meddata.anthesia.io.MEDDATA_TIMEOUT(optional) — request timeout in seconds, default30.
Client configuration
Claude Desktop
Add to claude_desktop_config.json (Settings → Developer → Edit Config):
Cursor
Add the same block to ~/.cursor/mcp.json (or the project .cursor/mcp.json).
Smithery (hosted, no install)
The server is hosted on Smithery, so MCP clients that support Smithery can connect without installing anything. You provide your MedData API key in the Smithery config and it routes to the server.
LangChain / LangGraph
Any LangChain or LangGraph agent can use these tools through
langchain-mcp-adapters:
LlamaIndex works the same way via its MCP tool spec.
Develop from source
Notes
- Data is for informational purposes only and is not medical advice.
- Interaction data comes from established medical databases; an empty result means none were found in those sources, not that a combination is proven safe.
來源:README.md,提交 a0ab4de
工具
0版本歷史
1- v0.2.1最新Sep 16, 2026
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