# Digbi Health

**Canonical:** https://apis.io/providers/digbi-health/  
**Website:** https://digbihealth.com/  
**APIs profiled:** 0

Digbi Health is a digital therapeutics company delivering a precision-biology virtual clinic for food-related and inflammatory illnesses — obesity, cardiometabolic disease, type 2 diabetes, digestive disorders (IBS, GERD), MSK chronic pain, PCOS, sleep and mental health. Its FoodRx program combines host-genetics and gut-microbiome testing with app-based coaching, precision nutrition, and pre/probiotic therapies, delivered to members through health plans and employers. Digbi Health is backed by Accel. The company operates a consumer-facing storefront and member app rather than a public developer API; this profile captures the public web, agent, and security surfaces observable at digbihealth.com.

## Kin Score — 14.4 / 100 (emerging)

Scored 2026-08-17 under rubric 0.11.0. Trend: flat (+0.0 from 14.4).

| Facet | Score |
|---|---|
| Discoverability | 57.4 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 6.5 |
| Commercial Clarity | 34.2 |

Regulatory layer — **Health**: 17.5 (matched via tags).

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Access

Unknown — onboarding: unknown, pricing: unknown, trial: no (confidence: low).

## Security (1)

- **Digbi Health Domain Security** — TLSv1.3 · HSTS · DMARC

## Tags

Company, Health, Digital Therapeutics, Precision Medicine, Genomics, Microbiome, Nutrition, Chronic Care, Telehealth

---

Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/digbi-health/). Scores are computed from the provider's own public artifacts under a published rubric.