Privacy-preserving synthetic health data generation. FHIR R4/R5 compliant.
Quick Install
Automated & IDE SetupCopy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
One-click editor setup isn’t available for this listing yet — we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.
Manual Client & Custom JSON ConfigExpand JSON ▾
No confirmed setup config for this listing yet. We only publish a config block when the install details come from the project itself — its README, its docs, or a verified owner. We haven’t found those for K01 Synthetic Health Data, and we’d rather show nothing than a guess you’d paste into your client. Follow the project’s own setup instructions for the current steps.
Capabilities & Tool Schemas (6)
Inspect callable tools, capabilities, and parameters exposed to AI agents by K01 Synthetic Health Data.
generate_synthetic_cohortGenerate synthetic patient cohorts with demographic and clinical constraints
search_patientsSearch a virtual patient database with advanced healthcare filters
get_patient_recordRetrieve a complete patient record with medication and condition summaries
get_patient_medicationsGet detailed medication records with ATC codes and therapeutic indications
get_patient_conditionsRetrieve patient conditions with ICD-10 codes and localized names
compare_fhir_versionsCompare the same patient data across FHIR R4 and R5
Documentation Overview
K01 MCP Server
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. No real patient data is involved at any point.
This repository contains documentation and configuration for the K01 MCP server. The server implementation is proprietary and runs on K01 infrastructure.
Available Tools
| Tool | Description | Key Parameters |
|---|---|---|
generate_synthetic_cohort | Generate synthetic patient cohorts with demographic and clinical constraints | count, age_min/age_max, gender, condition (ICD-10), seed, locale |
search_patients | Search a virtual patient database with advanced healthcare filters | gender, birthdate, numberOfMedicinesFrom/To, conditionTypes, locale |
get_patient_record | Retrieve a complete patient record with medication and condition summaries | patient_id, fhir_version |
get_patient_medications | Get detailed medication records with ATC codes and therapeutic indications | patient_id, seed, fhir_version |
get_patient_conditions | Retrieve patient conditions with ICD-10 codes and localized names | patient_id, seed, fhir_version |
compare_fhir_versions | Compare the same patient data across FHIR R4 and R5 | patient_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):
Cursor
Add to your Cursor MCP configuration (.cursor/mcp.json):
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:
Search for complex patients
"Find patients with 3+ medications and chronic conditions"
Compare FHIR versions
"How do this patient's medications look in R4 vs R5?"
See docs/examples.md for more workflows.
Privacy and Security
All data generated by K01 is fully synthetic. No real patient data is used, stored, or referenced at any point in the pipeline.
- Differential privacy — noise injection with configurable epsilon values ensures generated distributions cannot be reverse-engineered to identify real individuals
- No training on real data — the generation models are built from published clinical statistics and pharmacological references, not patient records
- 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.
Related MCP Servers
Adoption & maintenance
Factual signals from GitHub, npm, and our automated checks — not a rating.
GitHub stars
1
Stargazers on the source repository.
Last commit
6mo ago
Most recent push to the default branch.
Tools exposed
6
Callable tools this server registers over MCP.
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Frequently Asked Questions about K01 Synthetic Health Data
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