Cure Cancer With AI

io.github.hifarrer由 GitHub 帳號 hifarrer 發布v1.0.0更新於 Oct 24, 2026

Free oncology data (research, trials, FDA approvals, news) plus IBM MAMMAL biomedical predictions.

已驗證Streamable HTTP可網頁執行知識與記憶資料與分析AI 與機器學習

概覽

AI 產生的概覽

遠端 MCP 伺服器,提供腫瘤學資料(PubMed 論文、新聞、FDA 核准、臨床試驗)以及 IBM MAMMAL 生物醫學預測。

可以做什麼
  • 跨所有資料集一次搜尋研究論文、新聞、部落格文章、FDA 核准與臨床試驗
  • 列出並取得腫瘤學研究論文、新聞、部落格文章、FDA 核准藥物與臨床試驗,可依癌症類型、關鍵字、狀態或日期篩選
  • 依 id、slug 或 NCT 編號取得單篇論文、單篇部落格或單一試驗(含納入條件與地點)
  • 以 IBM MAMMAL 預測蛋白–蛋白交互作用、藥物–標靶結合親和力(pKd)與 ClinTox 試驗毒性
  • 依範例藥物或目標特性搜尋藥物化合物,並列出可用特性
  • 檢查 MAMMAL 預測模型是否已載入就緒
適用情境
適合需要查詢腫瘤學文獻、臨床試驗、FDA 藥物核准或癌症新聞,或對蛋白對、藥物–標靶對、化合物做快速生物醫學模型預測的情境。適用於需要乾淨 JSON 並使用免費金鑰的研究工具、儀表板與代理程式。
執行需求
遠端 Streamable HTTP 端點,無需本機安裝。需要從供應商網站取得免費 API 金鑰,並以 Authorization Bearer 權杖標頭送出。免費額度為每把金鑰每小時 100 次請求。需能連線至供應商主機。
安裝前請注意
API 金鑰是放在 Authorization 標頭中的機密,請勿寫入共用設定或日誌。MAMMAL 預測為 CPU 運算,可能耗時約 60 秒,有逾時風險。資料僅供參考,不構成醫療建議,呈現結果時應引用來源連結。查詢內容會傳送至第三方服務。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Cure Cancer With AI,將其新增到工作區。
  2. 連接 Authorization token 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
  3. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.hifarrer%2Fcure-cancer-with-ai/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "cure-cancer-with-ai": {
      "type": "http",
      "url": "https://www.curecancerwithai.com/api/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_TOKEN>"
      }
    }
  }
}

README

Cure Cancer With AI — Public API

A free public REST API and MCP server for oncology data: peer-reviewed research papers (PubMed), curated cancer news, FDA-approved oncology drugs, clinical trials, and a cross-dataset keyword search — plus IBM MAMMAL biomedical foundation-model predictions (protein–protein interaction, drug–target affinity, and ClinTox clinical-trial toxicity).

Base URL: https://www.curecancerwithai.com · Docs: https://www.curecancerwithai.com/developers · OpenAPI 3.1 spec · Agent instructions

[OpenAPI] [MCP] [License: MIT]


What it's for

If you need to programmatically access oncology research, clinical trials, FDA approvals, or cancer news, or to run biomedical model predictions (protein–protein interaction, drug–target binding affinity, drug toxicity), this API gives you clean JSON with a free API key. It's a good fit for research tools, dashboards, chatbots, and AI agents.

Quickstart

  1. Get a free API key — sign in at https://www.curecancerwithai.com/api-keys and click Create key (format ccw_live_..., shown once).
  2. Send it on every request as a Bearer token:
bash
curl "https://www.curecancerwithai.com/api/v1/search?q=osimertinib&types=research,fdaApprovals" \  -H "Authorization: Bearer ccw_live_YOUR_KEY"
  • Auth: Authorization: Bearer ccw_live_... (or x-api-key: ccw_live_...)
  • Free tier: 100 requests/hour per key (rolling window). Watch X-RateLimit-Remaining; on HTTP 429 wait for Retry-After.
  • List endpoints return { data: [...], pagination: {...} }; single-record endpoints return { data: {...} }; errors return { error: "..." }.

Endpoints

MethodPathDescription
GET/api/v1/researchPeer-reviewed oncology research papers (PubMed)
GET/api/v1/research/{idOrPubmedId}A single research paper
GET/api/v1/newsCurated cancer news
GET/api/v1/blogEditorial blog posts (excerpts)
GET/api/v1/blog/{slug}A single blog post (full content)
GET/api/v1/fda-approvalsFDA-approved oncology drugs
GET/api/v1/clinical-trialsClinical trials from public registries
GET/api/v1/clinical-trials/{nctId}A single trial (eligibility + locations)
GET/api/v1/searchCross-dataset keyword search (all datasets at once)
POST/api/v1/mammal/ppiMAMMAL: protein–protein interaction
POST/api/v1/mammal/dtiMAMMAL: drug–target interaction (pKd)
POST/api/v1/mammal/clintoxMAMMAL: ClinTox clinical-trial toxicity

Common query params on list endpoints: limit (1–100, default 20), offset, and usually cancerType, search, from/to. Full details and field lists are in the OpenAPI spec and AGENTS.md.

MCP server (for AI agents)

There's a remote Model Context Protocol server over Streamable HTTP that exposes every endpoint above as a tool, so Claude, ChatGPT, and other MCP clients can call the API directly.

  • Endpoint: https://www.curecancerwithai.com/api/mcp
  • Auth: send Authorization: Bearer ccw_live_YOUR_KEY as a header.
json
{  "mcpServers": {    "cure-cancer-with-ai": {      "url": "https://www.curecancerwithai.com/api/mcp",      "headers": { "Authorization": "Bearer ccw_live_YOUR_KEY" }    }  }}

Tools: search_oncology, list_research, get_research_paper, list_news, list_blog_posts, get_blog_post, list_fda_approvals, list_clinical_trials, get_clinical_trial, predict_ppi, predict_dti, predict_clintox, mammal_health. See mcp/.

Examples

Runnable samples in examples/: curl.sh, javascript.mjs, python.py. Import openapi.json into Postman or any OpenAPI tool, or use the Postman collection.

Disclaimer

All data is for informational purposes only and is not medical advice. Cite source URLs (url, fullTextUrl, labelPdfUrl) when presenting results to users.

Links

來源:README.md,提交 31cffff

工具

15

search_oncology

Search all oncology datasets

Search a keyword across every Cure Cancer With AI dataset at once — research papers, news, blog posts, FDA approvals, and clinical trials — with results grouped by type. Use this first for broad discovery, then fetch a single record by id/slug/nctId for full detail.

輸入參數q必填limittypescancerType

list_research

List research papers

List peer-reviewed oncology research papers ingested from PubMed (abstracts, authors, journal, plain-language summaries). Filter by cancer type, treatment type, keyword, or publication date.

輸入參數tofromlimitoffsetsearchcancerTypetreatmentType

get_research_paper

Get a research paper

Fetch a single research paper by its internal id or PubMed id.

輸入參數idOrPubmedId必填

list_news

List cancer news

List curated cancer news articles aggregated from trusted sources. Filter by cancer type, keyword, or published date.

輸入參數tofromlimitoffsetsearchcancerType

list_blog_posts

List blog posts

List editorial blog articles (excerpts). Use get_blog_post for full content. Filter by category, cancer-type tag, or keyword.

輸入參數limitoffsetsearchcategorycancerType

get_blog_post

Get a blog post

Fetch a single blog post by slug, including the full article content.

輸入參數slug必填

list_fda_approvals

List FDA approvals

List FDA-approved oncology drugs with indication, company, approval date, and label links. Filter by cancer type, keyword, or approval date.

輸入參數tofromlimitoffsetsearchcancerType

list_clinical_trials

List clinical trials

List clinical trials from public registries (conditions, status, intervention type). Filter by condition, status (e.g. RECRUITING), or keyword.

輸入參數limitoffsetsearchstatuscondition

get_clinical_trial

Get a clinical trial

Fetch a single clinical trial by NCT id (or internal id), including eligibility criteria and locations.

輸入參數nctId必填

predict_ppi

Predict protein–protein interaction

Predict the binding-affinity class for a pair of proteins using the IBM MAMMAL biomedical foundation model. Returns label "1" (interacting) or "0" (non-interacting). Inference is CPU-bound and may take up to ~60s.

輸入參數protein_a必填protein_b必填

predict_dti

Predict drug–target interaction (pKd)

Predict drug–target binding affinity as pKd (−log10 Kd; higher = stronger binding) using IBM MAMMAL. Inference is CPU-bound and may take up to ~60s.

輸入參數drug_seq必填norm_y_stdtarget_seq必填norm_y_mean

predict_clintox

Predict clinical-trial toxicity (ClinTox)

Predict clinical-trial toxicity for a compound using IBM MAMMAL. Returns pred 1 (toxic / likely to fail trials) or 0 (not toxic) plus a raw score. Inference is CPU-bound and may take up to ~60s.

輸入參數smiles必填

search_compounds

Search pharmaceutical compounds

Find pharmaceutical compounds two ways: by example drugs you already know (fuzzy-matched), or by setting target characteristics on a −4…+4 scale. Provide exactly one of `examples` or `preferences`. Use list_compound_characteristics for the available preference names.

輸入參數limitexamplespreferencesinclude_characteristics

list_compound_characteristics

List compound characteristics

List the pharmaceutical-compound characteristics (each scored on the −4…+4 scale) that can be used as preference keys in search_compounds.

無需輸入參數。

mammal_health

Check MAMMAL model health

Check whether the IBM MAMMAL prediction model is loaded and ready. No API key required. Call this before predict_* tools if a prior prediction timed out.

無需輸入參數。

版本歷史

1
  1. v1.0.0最新Sep 16, 2026

評分

已滿足適用檢查項的 90%

該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通必需25 分
  • 已宣告認證方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 圖示10 分
  • 文件15 分
  • 授權條款10 分

    請在儲存庫或註冊中心條目中宣告授權條款。