Open-source guardrails between AI agents and FHIR clinical data — PHI redaction, immutable audit, step-up auth, tenan...
Copy the install, test the workflow, then decide if it earns a permanent slot.
Still active enough to matter. Good candidate for a fast stack test instead of a long evaluation loop.
Copy the install, test the workflow, then decide if it earns a permanent slot.
You can test this quickly and remove it cleanly if it misses.
GitHub health 100/100. no security policy. Fresh enough repo health and manageable issue load keep the risk controlled.
AI Agent
Universal
Model
Gemini
Fastest way to find out if HealthClawGuardrails belongs in your setup.
Copy the install command, run a real test, and back it out cleanly if it slows you down.
claude mcp add healthclawguardrails -- npx healthclawguardrailsRun this first. You will know quickly if the workflow earns a permanent slot.
claude mcp remove healthclawguardrailsNo messy cleanup loop. If it misses, remove it and keep moving.
Install Location
~/ └─ .claude.json └─ mcp_servers/ └─ healthclawguardrails ← registers here
Open-source guardrails between AI agents and FHIR clinical data — PHI redaction, immutable audit, step-up auth, tenant isolation. MCP server + OpenAI/Gemini adapters. A healthclaw.io project.
Source: GitHub repository
Source check: July 18, 2026
Upstream commit: July 17, 2026
Repository state: Not marked archived
Honeystax upvotes are community interest signals, not star ratings. GitHub stars and repository health are source measurements; editorial risk and trial-cost notes are Honeystax analysis.