FHIR standardized health data. MCP standardized how AI connects to tools. HealthClaw standardizes the security, privacy, and clinical safety guardrails in between.
When an AI agent accesses clinical data through HealthClaw, each request is validated, redacted, authorized, and recorded before anything touches the FHIR server.
Applied on every read path: direct reads, search results, upstream proxy responses, and context envelopes. Agents work with safe, de-identified data by default.
Whether you're building an AI health agent, managing your own health data, or evaluating compliance infrastructure — HealthClaw meets you where you are.
uv sync && python main.py — running in 10 secondsCuratr evaluates FHIR resources against live public terminology services, explains issues in plain language, and lets you approve fixes with full provenance tracking.
Every approved fix creates a linked Provenance resource
recording patient intent, field changes, and agent attribution — recorded in the immutable audit trail. No black-box corrections.
HealthClaw works with any FHIR server. The guardrails are the product, not the data layer.
| HealthClaw | AWS HealthLake | Medplum MCP | Raw FHIR | |
|---|---|---|---|---|
| Any FHIR server | ✓ | ✗ | ✗ | — |
| PHI redaction on reads | ✓ | ✗ | ✗ | ✗ |
| Immutable audit trail | ✓ | Separate | Partial | ✗ |
| Step-up auth for writes | ✓ | Separate | Built-in | ✗ |
| Human-in-the-loop | ✓ | ✗ | ✗ | ✗ |
| R6 Permission $evaluate | ✓ | ✗ | ✗ | ✗ |
| Setup time | 10 sec | 30+ min | 15+ min | Varies |
No accounts. No API keys. No cloud setup. Clone, install, run.
# Install + run in 10 seconds uv sync STEP_UP_SECRET=your-secret python main.py # Or with Docker docker-compose up -d --build # Connect to your FHIR server FHIR_UPSTREAM_URL=https://hapi.fhir.org/baseR4 python main.py
The current health data system was built around institutions, not patients. What happens when we flip that?
Read on Substack →A walkthrough of building an AI health agent using OpenClaw skills and HealthClaw Guardrails with real health data.
Read on Substack →