Wellness Nourish

by davidmosiah

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Description

<h1 align="center">Wellness Nourish</h1> <div align="center"> <img src="assets/banner.png" alt="Wellness Nourish — Nourish MCP for AI agents" width="85%" /> </div> <h3 align="center"> Local-first nutrition MCP — food search, barcode lookup…

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Details

Author: davidmosiah
Downloads: 263
Categories: Other

- Food search via USDA FoodData Central
- Packaged‑food barcode lookup via Open Food Facts
- Local barcode image decoding with ZXing
- Photo‑assisted meal estimation (agent describes visible items)
- Local estimator with a pt‑BR/Brazilian‑food catalog
- Intake logging with preview mode (log --preview)
- Hydration and goal tracking
- Daily and weekly summaries, exports, meal memory
- Coach‑style nutrition workflows (“what should I eat now?”)

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Wellness Nourish

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "wellness nourish": {
            "nourish": {
                "command": "npx",
                "args": [
                    "-y",
                    "wellness-nourish"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "wellness nourish": {
            "nourish": {
                "command": "npx",
                "args": [
                    "-y",
                    "wellness-nourish"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "wellness nourish": {
            "nourish": {
                "command": "npx",
                "args": [
                    "-y",
                    "wellness-nourish"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "wellness nourish": {
            "nourish": {
                "command": "npx",
                "args": [
                    "-y",
                    "wellness-nourish"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "wellness nourish": {
            "nourish": {
                "command": "npx",
                "args": [
                    "-y",
                    "wellness-nourish"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "wellness nourish": {
            "nourish": {
                "command": "npx",
                "args": [
                    "-y",
                    "wellness-nourish"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "wellness nourish": {
            "nourish": {
                "command": "npx",
                "args": [
                    "-y",
                    "wellness-nourish"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "wellness nourish": {
            "nourish": {
                "command": "npx",
                "args": [
                    "-y",
                    "wellness-nourish"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "wellness nourish": {
            "nourish": {
                "command": "npx",
                "args": [
                    "-y",
                    "wellness-nourish"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "wellness nourish": {
            "nourish": {
                "command": "npx",
                "args": [
                    "-y",
                    "wellness-nourish"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "wellness nourish": {
            "nourish": {
                "command": "npx",
                "args": [
                    "-y",
                    "wellness-nourish"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "wellness nourish": {
            "nourish": {
                "command": "npx",
                "args": [
                    "-y",
                    "wellness-nourish"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "wellness nourish": {
            "nourish": {
                "command": "npx",
                "args": [
                    "-y",
                    "wellness-nourish"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "wellness nourish": {
            "nourish": {
                "command": "npx",
                "args": [
                    "-y",
                    "wellness-nourish"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "wellness nourish": {
            "nourish": {
                "command": "npx",
                "args": [
                    "-y",
                    "wellness-nourish"
                ]
            }
        }
    }
}

From the repository

Install via npm and run the stdio MCP server with npm start or via CLI commands such as npx -y wellness-nourish search banana. For Streamable HTTP, run node dist/index.js --http. One‑command setup is available for Hermes (npx -y delx-wellness-hermes setup) and OpenClaw (npx -y delx-wellness-openclaw setup). Configure environment variables like FDC_API_KEY and NOURISH_OFF_ENABLED for optional providers, or use NOURISH_FIXTURE_MODE=1 to demo offline with bundled fixtures.

`nourish_agent_manifest`

Return agent-facing install, safety, resource, and first-call guidance.

`nourish_capabilities`

Describe supported nutrition workflows, providers, and recommended first tools.

`nourish_connection_status`

Report local storage, fixture, USDA, and Open Food Facts readiness without returning secrets.

`nourish_quickstart`

Personalized 3-step setup walkthrough for the human user. Adapts to current state (USDA key set? OFF enabled? local-dir writable?). Call this first when the user asks 'how do I use this?'

`nourish_demo`

Returns synthetic example payloads of nourish_search_food, nourish_estimate_meal, and nourish_daily_summary so agents see the contract before any real call. Shapes are verified against the real pipelines by scripts/demo-contract-test.mjs, so they are safe to write a parser against; `inputs` shows the call that produced each sample.

`nourish_privacy_audit`

Describe local storage, secret handling, source licensing, and safety boundaries.

`nourish_profile_get`

Returns the shared Delx Wellness profile (~/.delx-wellness/profile.json). Read-only. Surfaces calorie/macro targets, dietary preferences, restrictions/allergies, and goals so nourish coach/suggest tools can personalize meals.

`nourish_profile_update`

Persist a partial patch to the shared Delx Wellness profile. Requires explicit_user_intent: true. Rejects any field containing oauth/token/secret/password/cookie/refresh/api_key/session — the profile is for non-secret wellness context only.

`nourish_onboarding`

Returns the 11-question onboarding flow for the shared Delx Wellness profile. Read-only. The agent should ask these questions next so wellness-nourish (and the rest of the wellness stack) can personalize responses — non-secret data only, stored at ~/.delx-wellness/profile.json.

`nourish_search_food`

Search food providers by query. Use taco or br_local for Brazilian staples, open_food_facts for packaged products, usda for generic foods, or all.

`nourish_lookup_barcode`

Lookup a packaged food barcode in Open Food Facts.

`nourish_decode_barcode_image`

Decode a barcode from an image path, base64 image, or data URI without logging intake.

`nourish_lookup_barcode_image`

Decode a packaged-food barcode image, then lookup the product in Open Food Facts.

`nourish_get_food`

Fetch a USDA food by source_id, an Open Food Facts food by barcode source_id, or a TACO food by source_id.

`nourish_estimate_meal`

Estimate nutrition for a short meal text using local deterministic defaults. Accepts text or meal_text; preserve unresolved and confidence.

`nourish_estimate_meal_photo`

Estimate meal nutrition from an agent-provided photo observation; always requires user confirmation before logging.

`nourish_analyze_food_image`

Route agent-provided food image observations across barcode, nutrition label OCR, or meal-photo estimation without logging.

`nourish_log_intake`

Log an intake entry only after explicit user intent. Pass explicit_user_intent: true after the user asks to save/log/register; accepts text or meal_text plus structured food data.

`nourish_daily_coach`

Summarize today, goal gaps, wearable context, and a safe next action for Telegram-style coaching.

`nourish_suggest_next_meal`

Suggest a next meal from today's intake, goals, personal memory, and optional wearable context.

`nourish_after_log_review`

Review the day after a meal log and explain what changed plus the next correction or action.

`nourish_pre_workout_nutrition`

Suggest light pre-workout nutrition using goals, current intake, and optional WHOOP/Garmin context.

`nourish_evening_checkin`

Check late-day protein, calories, and hydration gaps with a compact Telegram-friendly next step.

`nourish_pull_wearable_context`

Read the most recent shared wellness_context (delx-wellness-context/v1) written by a wearable connector to ~/.delx-wellness/, so coach tools can be recovery/strain-aware without the agent passing it inline. Read-only; never fabricates wearable data. If no connector has persisted a context yet, returns available:false with the expected path. The returned context can be passed straight into nourish_daily_coach / nourish_suggest_next_meal / nourish_pre_workout_nutrition as wearable_context (or set auto_wearable:true on those tools to pull it automatically).

`nourish_remember_meal`

Save a personal meal shortcut locally after explicit user intent, for example 'meu cafe normal' -> '2 ovos e banana'.

`nourish_list_memory`

Read local remembered meals and nutrition preferences for personal Telegram shortcuts.

`nourish_forget_memory`

Delete a local remembered meal by id or label after explicit user intent.

`nourish_update_intake`

Update a local intake entry by id. Quantity or grams_estimate changes rescale nutrients to keep summaries consistent. Gated: requires explicit user intent — agents must not call this autonomously.

`nourish_list_intake`

List local intake entries with optional filters: date OR since/until range, meal_type, tag, source_trace, min_confidence, limit. All filters AND together. Returns most-recent-first.

`nourish_delete_intake`

Delete a local intake entry by id. Gated: requires explicit user intent — agents must not call this autonomously.

`nourish_clear_day`

Delete all local intake entries for a date after explicit user intent.

`nourish_delete_water`

Delete a single local hydration entry by id after explicit user intent.

`nourish_clear_hydration_day`

Delete all local hydration entries for a date after explicit user intent. Does not touch intake — pair with nourish_clear_day or use nourish_clear_day { include_hydration: true } for both.

`nourish_carbon_summary`

Estimate the carbon footprint (kg CO2-equivalent) of a meal, plus optional lower-carbon swap suggestions. Pass `items: [{name, grams}, ...]` for an arbitrary meal, OR `date: YYYY-MM-DD` to compute carbon over that day's logged intake. Data: Agribalyse 3.1 (Etalab Open License) + Our World in Data / Poore & Nemecek 2018 (CC-BY 4.0). Read-only; never mutates state.

`nourish_undo_last`

Undo the most recently logged intake or hydration entry. The most common Telegram/agent recovery move ('I logged the wrong thing'). Returns what was undone so the agent can confirm. Requires explicit_user_intent. Pass kind: 'intake' | 'hydration' | 'any' (default 'any') to scope the undo.

`nourish_log_water`

Log local hydration in milliliters after explicit user intent. Pass explicit_user_intent: true after the user asks to save/log water.

`nourish_hydration_summary`

Summarize local hydration for a date.

`nourish_get_goals`

Read local calorie, macro, and hydration goals.

`nourish_set_goals`

Set local calorie, macro, and hydration goals after explicit user intent. Use daily: {...} or flat shortcuts like calories_kcal/protein_g; pass explicit_user_intent: true after confirmation.

`nourish_goal_progress`

Compute per-day progress vs configured goals (kcal, protein, carbs, fat, water) for today / yesterday / last_7_days / last_30_days. Returns per-day breakdown (consumed, goal, pct, delta_to_goal), period totals, multi-day averages, days_on_target count, and locale-aware next-action recommendations (pt-BR if profile language is Portuguese, otherwise en). Read-only: no logging side effects, no explicit_user_intent required.

`nourish_daily_summary`

Summarize local intake totals, confidence, and source coverage for a date. Pass `compare_to: 'yesterday'` or `compare_to: '7d_avg'` to add a `comparison` block with per-nutrient deltas — useful for trend coaching ('your protein is low again — third day in a row').

`nourish_compare_days`

Compute a per-nutrient diff between two days' summaries. Returns deltas (date_b - date_a) for calories, protein, carbs, fat, fiber, sugar, sodium plus what changed by meal type. Useful for 'how was today vs yesterday?' coaching.

`nourish_bulk_log_intake`

Log multiple intake entries in a single call. Requires explicit user intent (explicit_user_intent: true). Each item is processed through the same text-estimator pipeline as `nourish_log_intake`, but the entire batch shares one intent flag — perfect for Telegram users who say 'log everything I ate today: breakfast was X, lunch was Y, dinner was Z'. Returns per-item success/failure so a partial failure doesn't lose the rest.

`nourish_weekly_summary`

Summarize seven days of local intake totals from a start date.

`nourish_export_data`

Export local intake data as JSONL or CSV without provider secrets or tokens. Defaults to the 500 most-recent rows; pass since/until to scope by date or max_rows to widen/narrow. Omitted rows are reported so you can refine instead of dumping months of history into chat (use the `wellness-nourish export` CLI for a full unbounded dump).

`nourish_chatgpt_dashboard`

Open an interactive ChatGPT/MCP Apps dashboard for today's nutrition summary, safe meal estimation, and next-meal coaching. Read-only; logging still requires explicit user confirmation through existing tools.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "wellness nourish": {
            "nourish": {
                "command": "npx",
                "args": [
                    "-y",
                    "wellness-nourish"
                ]
            }
        }
    }
}

McpServers

{
    "nourish": {
        "command": "npx",
        "args": [
            "-y",
            "wellness-nourish"
        ]
    }
}

<h1 align="center">Wellness Nourish</h1>

<h3 align="center">
Local-first nutrition MCP — food search, barcode lookup, intake logging, hydration. Works without OAuth.<br>
Local-first MCP server — <strong>tokens never leave your machine</strong>.
</h3>

<p align="center">
<strong>📈 Published on npm and used by AI agents and MCP clients</strong> — see the live <a href="https://www.npmjs.com/package/wellness-nourish">download badge</a> above for current numbers.<br>
<sub>If Nourish helps your agent, a ⭐ on this repo makes it easier for other AI builders to find.</sub>
</p>

> ⚡ One-command install — pick your runtime:
> - Delx Wellness for Hermes: npx -y delx-wellness-hermes setup
> - Delx Wellness for OpenClaw: npx -y delx-wellness-openclaw setup
>
> Both preconfigure this connector and the full Delx Wellness stack into a dedicated profile. Or wire it standalone into Claude Desktop / Cursor / ChatGPT Desktop — see the install section below.
>
> Want runnable agent examples? Use the Delx Agent Workbench for prompt packs, MCP client configs and local-first workflow templates.

---

Overview

Wellness Nourish is a local MCP server for nutrition search, barcode lookup, barcode photo lookup, photo-assisted meal estimation, intake logging, hydration, goals, exports, daily or weekly summaries, personal meal memory, and coach-style nutrition workflows. It runs over stdio by default for MCP clients and can also run a Streamable HTTP endpoint at POST /mcp.

> If this nutrition layer helps your agent workflow, please star the repo. Stars make the project easier for other AI builders to discover and help Delx keep shipping local-first wellness infrastructure.

Field guide: Why local-first wellness agents need MCP.

Try It In 60 Seconds

npx -y wellness-nourish doctor
npx -y wellness-nourish search banana
npx -y wellness-nourish barcode 0000000000000
npx -y wellness-nourish log --preview "2 ovos, banana e café preto"

Demo (offline, no API key)

NOURISH_FIXTURE_MODE=1 serves the bundled fixtures/ instead of calling
USDA or Open Food Facts, so you can see the exact shape of every response with
zero network access or keys. The outputs below are captured verbatim from this
mode:

$ NOURISH_FIXTURE_MODE=1 wellness-nourish search banana
Bananas, raw	usda	89 kcal/100g
BANANA	usda	312 kcal/100g

$ NOURISH_FIXTURE_MODE=1 NOURISH_OFF_ENABLED=1 wellness-nourish barcode 737628064502

{
  "name": "Peanut Butter",
  "barcode": "737628064502",
  "brand": "Fixture Foods",
  "serving": { "quantity": 1, "unit": "serving", "grams": 32 },
  "nutrients_per_serving": {
    "calories_kcal": 188.16,
    "protein_g": 8,
    "carbohydrates_g": 6.4,
    "fat_g": 16,
    "fiber_g": 1.92,
    "sugar_g": 2.88,
    "saturated_fat_g": 3.2,
    "sodium_mg": 128
  },
  "license": { "name": "Open Food Facts ODbL" },
  "data_quality": { "completeness": "high", "confidence": 0.75, "warnings": [] }
  // ...full record also includes nutrients_per_100g, available_portions, carbon
}

log --preview estimates a meal locally without writing anything:

$ wellness-nourish log --preview "2 eggs and a banana"

{
  "would_write": false,
  "total_nutrients": {
    "calories_kcal": 248.02,
    "protein_g": 13.89,
    "carbohydrates_g": 27.65,
    "fat_g": 9.89,
    "fiber_g": 3.07,
    "sugar_g": 14.43
  },
  "confidence": 0.7,
  "warnings": ["Nutrition values are estimates from simple food defaults."]
  // ...full record also includes per-item breakdown and entry_preview
}

For the full Telegram/Hermes flow:

npx -y delx-wellness-hermes setup
hermes -p delx-wellness

The connector uses USDA FoodData Central as the primary food search provider. Open Food Facts is used for packaged-food barcode lookup and product-name search when enabled. Local barcode image decoding is supported with ZXing. Meal photos are estimated only from an agent-provided visual observation and always require confirmation before logging. The local estimator includes a pt-BR/Brazilian-food catalog for common meals, kitchen units, and shortcuts such as arroz, feijão, frango, ovos, banana, tapioca, picanha, feijoada and salada. It does not provide hosted sync, autonomous photo upload, recipe generation, or medical advice.

Install

npm install
npm run build

Run the MCP server over stdio:

npm start

Run Streamable HTTP locally:

node dist/index.js --http

ChatGPT App / MCP Apps UI

Nourish also exposes a compact MCP Apps-compatible dashboard for ChatGPT and other compatible hosts:

- Tool: nourish_chatgpt_dashboard
- UI resource: ui://widget/nourish-dashboard-v1.html
- MIME type: text/html;profile=mcp-app

The dashboard shows the daily nutrition summary, hydration progress, profile gaps and next-meal coaching, and it can call nourish_estimate_meal from the embedded UI for preview-only estimates. It does not write intake, water or goals; mutating tools still require explicit user confirmation through the normal MCP tools.

Optional environment:

FDC_API_KEY=your_usda_key
NOURISH_OFF_ENABLED=1
NOURISH_LOCAL_DIR=~/.wellness-nourish
NOURISH_MCP_PORT=3000

Agents should never ask users to paste API keys, tokens, raw health exports, or private food logs into chat. Configure secrets through environment variables or local files.

CLI Commands

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Description

About

Details

Jump to

Setting up with Highlight

From the repository

nourish_agent_manifest

nourish_capabilities

nourish_connection_status

nourish_quickstart

nourish_demo

nourish_privacy_audit

nourish_profile_get

nourish_profile_update

nourish_onboarding

nourish_search_food

nourish_lookup_barcode

nourish_decode_barcode_image

nourish_lookup_barcode_image

nourish_get_food

nourish_estimate_meal

nourish_estimate_meal_photo

nourish_analyze_food_image

nourish_log_intake

nourish_daily_coach

nourish_suggest_next_meal

nourish_after_log_review

nourish_pre_workout_nutrition

nourish_evening_checkin

nourish_pull_wearable_context

nourish_remember_meal

nourish_list_memory

nourish_forget_memory

nourish_update_intake

nourish_list_intake

nourish_delete_intake

nourish_clear_day

nourish_delete_water

nourish_clear_hydration_day

nourish_carbon_summary

nourish_undo_last

nourish_log_water

nourish_hydration_summary

nourish_get_goals

nourish_set_goals

nourish_goal_progress

nourish_daily_summary

nourish_compare_days

nourish_bulk_log_intake

nourish_weekly_summary

nourish_export_data

nourish_chatgpt_dashboard

Claude Desktop / Cursor

McpServers

Overview

Try It In 60 Seconds

Demo (offline, no API key)

Install

ChatGPT App / MCP Apps UI

CLI Commands

Install

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FastMCP v2 🚀

`nourish_agent_manifest`

`nourish_capabilities`

`nourish_connection_status`

`nourish_quickstart`

`nourish_demo`

`nourish_privacy_audit`

`nourish_profile_get`

`nourish_profile_update`

`nourish_onboarding`

`nourish_search_food`

`nourish_lookup_barcode`

`nourish_decode_barcode_image`

`nourish_lookup_barcode_image`

`nourish_get_food`

`nourish_estimate_meal`

`nourish_estimate_meal_photo`

`nourish_analyze_food_image`

`nourish_log_intake`

`nourish_daily_coach`

`nourish_suggest_next_meal`

`nourish_after_log_review`

`nourish_pre_workout_nutrition`

`nourish_evening_checkin`

`nourish_pull_wearable_context`

`nourish_remember_meal`

`nourish_list_memory`

`nourish_forget_memory`

`nourish_update_intake`

`nourish_list_intake`

`nourish_delete_intake`

`nourish_clear_day`

`nourish_delete_water`

`nourish_clear_hydration_day`

`nourish_carbon_summary`

`nourish_undo_last`

`nourish_log_water`

`nourish_hydration_summary`

`nourish_get_goals`

`nourish_set_goals`

`nourish_goal_progress`

`nourish_daily_summary`

`nourish_compare_days`

`nourish_bulk_log_intake`

`nourish_weekly_summary`

`nourish_export_data`

`nourish_chatgpt_dashboard`