mcpField
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Munch

Munch

Remote
munch.businessHealth0Updated today

About Munch

Munch is a remote nutrition-tracking service for people who want to record meals and manage personal or household food plans. Its authenticated tools cover food lookup, confirmed meal logging, nutrition history, recipes, groceries, goals, water, and weight.

Key features

  1. 01Search foods and scan barcodes
  2. 02Review meals before confirmed logging
  3. 03Track nutrition history, water, weight, and goals
  4. 04Save recipes and plan meals
  5. 05Manage grocery lists and household recipes

Use cases

  1. 01Look up packaged food or ingredients
  2. 02Confirm and record a meal
  3. 03Plan household recipes and grocery lists
  4. 04Review nutrition trends and personal goals

MCP support

The remote MCP endpoint provides authenticated tools to manage nutrition records and related account data. It requires user confirmation before permanently logging prepared meal reviews; it does not provide medical advice.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://munch.business/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

Details

From the project README

Munch

Munch is a production remote Model Context Protocol service for personal nutrition tracking. It gives ChatGPT and compatible MCP clients authenticated tools for food lookup, meal review and confirmation, persistent nutrition history, saved foods, recipes, meal planning, grocery lists, goals, water, weight, account controls, and household collaboration.

Production website: https://munch.business

Production MCP endpoint: https://munch.business/mcp

Product model

Munch has a permanent Free tier and an optional Premium subscription. Premium is purchased and managed only through the Munch website. The ChatGPT connection flow, MCP tool descriptions, tool results, and embedded widgets do not advertise pricing or initiate checkout.

Munch is a consumer wellness product. It provides factual nutrition records and source-aware estimates; it does not provide medical advice, diagnosis, treatment, emergency guidance, or clinical dosing.

Current capabilities

  • Search USDA FoodData Central and Open Food Facts, including barcode lookup.
  • Cache provider results in Railway PostgreSQL while preserving immutable source snapshots in confirmed records.
  • Prepare meal reviews from ChatGPT-supplied food candidates and require explicit confirmation before permanent logging.
  • Store structured meals, food items, nutrients, assumptions, provenance, water, weight, and goals.
  • Save and reuse confirmed foods.
  • Create, search, revise, archive, log, and plan personal and household recipes, import recipes from public URLs with a review step, and manage grocery lists.
  • Export account data, revoke MCP connections, and delete an account through authenticated controls.
  • Render self-contained ChatGPT widgets for summaries, trends, confirmation, and import workflows.

Architecture

  • Runtime: Bun and Hono
  • MCP: @modelcontextprotocol/sdk
  • Authentication: Better Auth, passwordless email through Resend, and OAuth 2.1-compatible authorization for MCP clients
  • Database: Railway PostgreSQL with forced row-level security for user and household data
  • Billing: Stripe Checkout and Customer Portal on the Munch website
  • Food providers: USDA FoodData Central and Open Food Facts
  • Hosting: Railway, deployed from the main branch

Munch does not use Supabase at runtime.

Privacy and security boundaries

Munch derives user identity from the authenticated session or bearer token; MCP tools do not accept a selectable user identifier. Personal and household records are isolated in PostgreSQL using database roles and row-level security. Destructive operations require explicit confirmation and account deletion is tested against disposable accounts in CI.

Public policies and contacts:

  • Privacy: https://munch.business/privacy
  • Terms: https://munch.business/terms
  • Help: https://munch.business/help
  • Security: https://munch.business/security
  • Support: [email protected]
  • Security reports: [email protected]

Do not place credentials, personal nutrition data, or vulnerability details in public GitHub issues.

Local development

Requirements:

  • Bun 1.x
  • PostgreSQL 17-compatible database
  • Environment variables described in .env.example

Install and run:

bun install --frozen-lockfile
bun run db:migrate
bun run dev

Primary quality checks:

bun run format:check
bun run commerce:check
bun run submission:check
bun run typecheck
bun test

The full GitHub Actions suite also runs migrations twice for idempotency, Better Auth/OAuth smoke tests, reviewer-account readiness, nutrition and household RLS tests, recipe-planning tests, account export/deletion tests, operational readiness checks, and a production container build.

OpenAI submission package

Submission materials are version controlled in:

  • chatgpt-app-submission.json
  • docs/openai-submission/

The package includes listing copy, tool metadata, reviewer instructions, positive and negative test cases, and a release checklist. The production challenge token and reviewer password are intentionally excluded from Git.

Attribution

Munch began as a fork of Alexander Kutishevsky's MIT-licensed Nutrition MCP project. The hosted Munch service is independently developed and operated. See LICENSE and NOTICE.md for applicable notices.

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