# is.k01/synthetic-health-data

> Use this tool when you need to generate synthetic health data while preserving patient privacy, ideal for testing, training, and research applications that require FHIR R4/R5 compliant data. It solves problems related to data anonymization, security, and compliance, providing a safe and reliable alternative to real health data. Input parameters define the synthetic data's structure and output is a compliant, artificial dataset.

Canonical page: https://skillsregistry.net/skills/synthetic-health-data  
JSON: https://api.skillsregistry.net/v1/skills/synthetic-health-data

## Description

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

## Trust

- **Trust score (0–1):** 0.94
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/synthetic-health-data)
- **Repository:** <https://github.com/k01labs/k01-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "synthetic-health-data"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/synthetic-health-data` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/synthetic-health-data/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt