---
title: Nourish MCP nutrition module
description: Food lookup, barcode photo lookup, meal photo estimates, intake logs, hydration, goals, carbon summaries and nutrition trends for agents.
canonical: https://wellness.delx.ai/nutrition
content_signal: ai-train=no, search=yes, ai-input=yes
---

# Nourish MCP

Nourish is the Delx Wellness nutrition layer. It is a local-first MCP server for calories, macros, TACO/BR food search, barcode image decoding, meal photo previews, carbon context and nutrition trends, built to sit beside wearable connectors instead of pretending to be another device provider.

## Install

```bash
npx -y wellness-nourish setup --client claude
npx -y wellness-nourish doctor
```

## Agent client config

```json
{
  "mcpServers": {
    "nourish": {
      "command": "npx",
      "args": ["-y", "wellness-nourish@0.2.10"],
      "env": {
        "FDC_API_KEY": "${FDC_API_KEY}",
        "NOURISH_OFF_ENABLED": "1"
      }
    }
  }
}
```

## Hermes Telegram personal setup

```bash
npx -y wellness-nourish setup --client hermes --profile personal --local-dir /root/.hermes/nourish/personal
npx -y wellness-nourish doctor --client hermes --json
hermes mcp test nourish
```

This installs the Hermes skill at `~/.hermes/skills/nourish-mcp/SKILL.md` so Telegram meal messages, barcode photos and meal photo previews use confirmation-before-log by default.

## Workflows

- Preview a meal estimate before writing to the local log.
- Install Hermes personal mode for Telegram with setup --client hermes.
- Search TACO/BR local food data for Brazilian staples before falling back to USDA.
- Search USDA FoodData Central before estimating generic foods.
- Lookup packaged foods through Open Food Facts with ODbL attribution.
- Compare days, inspect trends, undo the last entry, or bulk-log a Telegram food recap.
- Summarize meal carbon footprint when food names have kg CO2e matches.
- Decode barcode photos from image paths, base64 images or data URIs before Open Food Facts lookup.
- Use agent vision observations for meal photo previews, then confirm portions before logging.
- Summarize calories, macros, hydration and goals in agent-friendly markdown.
- Export local intake data as JSONL or CSV.

## MCP tools

- `nourish_connection_status`
- `nourish_search_food`
- `nourish_lookup_barcode`
- `nourish_decode_barcode_image`
- `nourish_lookup_barcode_image`
- `nourish_estimate_meal`
- `nourish_estimate_meal_photo`
- `nourish_log_intake`
- `nourish_bulk_log_intake`
- `nourish_undo_last`
- `nourish_compare_days`
- `nourish_carbon_summary`
- `nourish_daily_summary`
- `nourish_weekly_summary`
- `nourish_log_water`
- `nourish_set_goals`
- `nourish_export_data`

## Resources

- `nourish://agent-manifest`
- `nourish://capabilities`
- `nourish://privacy-audit`
- `nourish://usage-guide`

## Privacy

- Food logs, hydration and goals stay under ~/.wellness-nourish unless NOURISH_LOCAL_DIR is set.
- No hosted account is required.
- Agents must preserve source attribution, confidence and safety warnings.
- Mutating MCP tools require explicit user intent.

## Known limits

- Nutrition estimates are approximate.
- Meal photo estimates depend on the agent vision layer and always require user confirmation before logging.
- No hosted sync or clinical guidance.
- Open Food Facts data carries attribution and share-alike obligations.
- TACO values ship as an attributed curated subset while redistribution-license confirmation remains a 1.0 gate.

## Links

- GitHub: https://github.com/davidmosiah/wellness-nourish
- npm: https://www.npmjs.com/package/wellness-nourish