K01 Synthetic Health Data

is.k01由 k01.is 發布官方發布者v1.7.1更新於 Oct 25, 2026

Privacy-preserving synthetic health data generation. FHIR R4/R5 compliant.

已驗證Streamable HTTP可網頁執行資料與分析AI 與機器學習

概覽

AI 產生的概覽

一個遠端 MCP 伺服器，讓助理產生並查詢兼顧隱私的合成 FHIR R4/R5 健康資料，供開發與測試使用。

可以做什麼
依年齡、性別、ICD-10 疾病等人口與臨床條件產生合成病患世代，可用種子確保可重現。依性別、出生日期、用藥數量和疾病類型搜尋虛擬病患資料庫。取得完整病患紀錄、含 ATC 代碼的用藥明細，以及含 ICD-10 代碼的疾病資訊。比較同一病患資料在 FHIR R4 與 R5 資源版本下的差異。
適用情境
適合需要具真實感但非真實病患資料來開發、測試、示範或分析 FHIR 應用時使用，也適合在不接觸正式健康紀錄的情況下比較 FHIR R4 與 R5 的紀錄差異。
執行需求
透過 streamable HTTP 連線至 mcp.k01.is 遠端端點。必須在 Authorization 標頭提供 Bearer API 金鑰；金鑰需聯絡 K01 取得，自助開通尚未提供。需要網路存取。
安裝前請注意
Authorization 中的 API 金鑰屬於機密，不應寫入共用設定。此伺服器為專有實作並執行於 K01 基礎設施，請求與參數會傳送給第三方。回傳資料皆為合成資料，不應視為真實臨床證據。產生與搜尋操作會耗用服務，可能受帳戶額度限制。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 K01 Synthetic Health Data，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/is.k01%2Fsynthetic-health-data/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": {
    "k01-synthetic-health-data": {
      "type": "http",
      "url": "https://mcp.k01.is/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_TOKEN>"
      }
    }
  }
}

README

K01 MCP Server

[License: MIT] [MCP]

Generate and query clinically realistic synthetic health data directly from your AI workflow.

K01's MCP server gives AI agents and LLM-powered tools access to privacy-preserving synthetic health data generation. Generate FHIR-compliant patient cohorts, query structured EHR data, and compare across FHIR versions — all with built-in differential privacy. The server never handles real patient records: it serves synthetic data from generators that were trained on real records, under differential privacy, inside a separate controlled environment.

This repository contains documentation and configuration for the K01 MCP server. The server implementation is proprietary and runs on K01 infrastructure.

Available Tools

ToolDescriptionKey Parameters
generate_synthetic_cohortGenerate synthetic patient cohorts with demographic and clinical constraintscount, age_min/age_max, gender, condition (ICD-10), seed, locale
search_patientsSearch a virtual patient database with advanced healthcare filtersgender, birthdate, numberOfMedicinesFrom/To, conditionTypes, locale
get_patient_recordRetrieve a complete patient record with medication and condition summariespatient_id, fhir_version
get_patient_medicationsGet detailed medication records with ATC codes and therapeutic indicationspatient_id, seed, fhir_version
get_patient_conditionsRetrieve patient conditions with ICD-10 codes and localized namespatient_id, seed, fhir_version
compare_fhir_versionsCompare the same patient data across FHIR R4 and R5patient_id, resource_type

All tools support both FHIR R4 and R5. See docs/tools.md for full parameter documentation.

Quick Start

Claude Desktop

Add to your Claude Desktop configuration (Settings > MCP Servers):

json
{  "mcpServers": {    "k01": {      "url": "https://mcp.k01.is/mcp",      "headers": {        "Authorization": "Bearer YOUR_API_KEY"      }    }  }}

Cursor

Add to your Cursor MCP configuration (.cursor/mcp.json):

json
{  "mcpServers": {    "k01": {      "url": "https://mcp.k01.is/mcp",      "headers": {        "Authorization": "Bearer YOUR_API_KEY"      }    }  }}

Restart the application after adding the configuration. The K01 tools will appear in the tool list.

Authentication

The K01 MCP server uses Bearer token authentication. Include your API key in the Authorization header.

To get an API key, contact K01 at k01.is. Self-service key provisioning is coming soon.

See docs/authentication.md for details.

Examples

Generate a diabetic cohort

"Generate 100 patients aged 40-65 with Type 2 diabetes"

The generate_synthetic_cohort tool creates a FHIR Bundle with Patient, Condition, MedicationStatement, Procedure, and Observation resources:

generate_synthetic_cohort(count=100, age_min=40, age_max=65, condition="E11.9", seed=42)

Search for complex patients

"Find patients with 3+ medications and chronic conditions"

search_patients(numberOfMedicinesFrom=3, conditionTypes="chronic", _count=20)

Compare FHIR versions

"How do this patient's medications look in R4 vs R5?"

compare_fhir_versions(patient_id="0101302989", resource_type="Medication")

See docs/examples.md for more workflows.

Privacy and Security

All data this server returns is fully synthetic. No real patient data passes through the server, is stored by it or is referenced by it.

  • Differential privacy — noise injection with configurable epsilon values ensures generated distributions cannot be reverse-engineered to identify real individuals
  • Real data stays behind the firewall — the generators are trained on real records under differential privacy inside a separate controlled environment; only the trained generators, never the records, are reachable from this server
  • FHIR-compliant output — all resources conform to HL7 FHIR R4/R5 specifications, making them safe drop-in replacements for real data in development and testing
  • Deterministic seeding — use seeds for reproducible results without persisting any patient data server-side

Links

License

This repository (documentation, configuration, and examples) is licensed under MIT. The K01 server implementation is proprietary.

來源：README.md，提交 51eacd7

工具

0
該伺服器需要 API 金鑰等憑證，因此 SourceWeft 無法在沒有憑證的情況下讀取其工具，也未收錄。

版本歷史

1
  1. v1.7.1最新Sep 16, 2026

評分

已滿足適用檢查項的 85%

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