K01 Synthetic Health Data

is.k01Published by k01.isOfficial publisherv1.7.1Updated Oct 25, 2026

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

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Overview

AI-generated overview

A remote MCP server that lets an assistant generate and query privacy-preserving synthetic FHIR R4/R5 health data for development and testing.

What you can do
Generate synthetic patient cohorts with demographic and clinical constraints such as age, gender and ICD-10 condition, with optional seeds for reproducibility. Search a virtual patient database by gender, birthdate, medication counts and condition types. Retrieve full patient records, medication details with ATC codes, and conditions with ICD-10 codes. Compare the same patient data across FHIR R4 and R5 resource versions.
When to use it
Useful when you need realistic but non-real patient data for FHIR-based development, testing, demos or analytics, or when you want to compare how records look across FHIR R4 and R5 without touching production health records.
Requirements
A remote endpoint at mcp.k01.is over streamable HTTP. A Bearer API key is required in the Authorization header; keys are obtained by contacting K01, with self-service provisioning not yet available. Network access is needed.
Before you install
The Authorization API key is a secret and must be kept out of shared configuration. The server is proprietary and runs on K01 infrastructure, so requests and parameters go to a third party. Returned data is synthetic, so it should not be treated as real clinical evidence. Generation and search actions consume the service and may be subject to account limits.

Installation

In SourceWeft

  1. Open K01 Synthetic Health Data in the dashboard and add it to a workspace.
  2. Connect Authorization token credentials. They are stored privately and never shown on public pages.
  3. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/is.k01%2Fsynthetic-health-data/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "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.

Source: README.md at commit 51eacd7

Tools

0
This server asks for a credential such as an API key, so SourceWeft could not read its tools without one and has not indexed them.

Version history

1
  1. v1.7.1LatestSep 16, 2026

Score

85% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
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  • Documentation15 pts
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