# USDA Nutrition Evidence Systematic Review

**Canonical:** https://apis.io/providers/nesr/  
**Website:** https://nesr.usda.gov/  
**APIs profiled:** 0

The Nutrition Evidence Systematic Review (NESR, formerly the Nutrition Evidence Library) is a team of systematic review methodology experts at the U.S. Department of Agriculture Center for Nutrition Policy and Promotion. It searches, evaluates and synthesizes scientific evidence on food and nutrition questions relevant to Federal policy and programs, including reviews for the Dietary Guidelines Advisory Committee, and publishes each completed review on its website.

## Kin Score — 5.7 / 100 (minimal)

Scored 2026-11-13 under rubric 0.28.0.

| Facet | Score |
|---|---|
| Discoverability | 44.6 |
| Contract Quality | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 4.8 |
| Access Clarity | 8.5 |

Regulatory layer — **Government & Public Sector**: 3.9 (matched via tags).

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | 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 |
| Delegated Identity | no |
| Protected Resource Metadata | no |
| Dynamic Client Registration | no |
| Agentic Commerce | no |
| Pagination Ratio | na |
| Operation Distinctiveness | na |
| MCP Tool Quality | na |

## Access

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

## Security (1)

- **USDA Nutrition Evidence Systematic Review Domain Security** — TLSv1.3 · DNSSEC · DMARC

## Tags

Government, Nutrition, Public Health, Systematic Reviews, Dietary Guidelines, Research

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