Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Pantry Relay find a vegetarian dinner for 2 using pantry stock, under 25 minutes"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A local household dinner handoff: plan from available food, reserve a chosen meal, remember it across sessions, and record cooking without double-counting inventory. Built with AI assistance as a candidate for the Amazon Developer Hackathon Alexa+ track. Not submitted, not an awarded project, and not an Amazon-certified integration.
Open the sample kitchen. No installation, login, paid model or cloud account is needed. This static demo uses the same pantry operations with SQLite compiled to WebAssembly through sql.js. Its fictional stock and meal plans stay in this browser's site storage; they are not synchronized between computers. Supported browsers coordinate tabs with Web Locks. Otherwise, use one tab at a time.
The public site demonstrates the pantry workflow. The real MCP endpoint runs separately in the local application below; the website does not provide a live Alexa session. To rebuild the static files from source, run npm run build:web after installing dependencies. GitHub Pages serves docs/.
Related MCP server: Gamito
Prerequisite: Node.js 24 or newer. No paid cloud account, API key, wallet, hardware, or subscription is required for this application.
npm ci
npm startOpen http://127.0.0.1:8767. Demo stock is fictional, with date labels relative to the first run. The SQLite file is in data/pantry.sqlite. To start a separate fictional household, set PANTRY_DB to a different file. PANTRY_PORT changes the local port.
Enter “Dinner for 2, vegetarian, under 25 minutes.” and choose Find dinner. Stock is unchanged.
Review the recipe, quantities and shortages. Choose Confirm dinner to reserve available ingredients. Shortages become shopping needs.
When that meal was actually cooked, choose Meal cooked. Reserved quantities are consumed once. Refresh: the pantry and meal history remain.
Plan for eight people to exercise shortages. Cancel dinner removes only that meal's reservations and shopping needs. Record real new stock before replanning.
The browser command input uses a small deterministic parser for serving count and minutes. It is not a hosted LLM or a live Alexa session. The recipe ranker uses pantry coverage and near-date stock. The real MCP service exposes that workflow to an agent chosen by the user; no hosted AI inference is bundled or charged by this application.
Connect a client that supports MCP 2025-11-25 Streamable HTTP to http://127.0.0.1:8767/mcp. The official MCP SDK serves JSON responses without a long-lived session. This is a local development configuration: it listens only on loopback and is not suitable for public deployment without household authentication.
Tools: pantry_snapshot, recommend_dinner, confirm_dinner, mark_meal_cooked, cancel_dinner, record_new_stock. It also provides the pantry://household/current resource and rescue-dinner prompt. Reusable agent guidance.
npm run demo
# Only on fictional demo data, to explicitly opt into state changes:
npm run demo -- --confirm-demoThe SDK client makes actual HTTP MCP calls. The report lists tool inputs and outputs; it does not pretend to be a live Alexa account. To change the endpoint, set PANTRY_MCP_URL.
npm testTwelve checks cover unchanged stock during proposals, exact-once cooking, stale proposals from overlapping users, cancellation, shortages, expiry changes, valid restocking, restart persistence, and the official MCP client over real HTTP. The integration test explicitly verifies protocol negotiation returns 2025-11-25. Browser-adapter checks use actual WebAssembly SQLite to verify persisted state, competing tabs, and failed storage writes without partial reservations.
Browser evidence is in evidence/. The recorded flow confirms a two-person skillet, records it cooked, reloads the app, and verifies the retained inventory. See verification record.
One household, one local computer; no user accounts or external transactions. Original demo recipes are not nutritional advice. Date labels organize stock; they do not establish food safety. Food recorded as received is not automatically substituted into an older plan: cancel and replan. Quantities use grams or whole-item counts. Multi-household hosting, nutritional recommendations, speech recognition, a general language-model agent and certified Alexa deployment are not implemented.
Public review video, 2 minutes 23 seconds, captioned with no audio. It uses actual browser captures and recorded MCP calls. A live Alexa session has not been tested. Local MP4.
Source code is offered under MIT; Bootstrap retains its own MIT notice in public/bootstrap-LICENSE.txt. Dependency licenses stay with their npm packages. No credentials, household database, or node_modules are included in the release archive.
This server cannot be deployed
Household-aware cooking brain: pantry, meal suggestions, dietary safety, recipes, shopping lists.
Scraps Kitchen gives any AI agent a persistent, household-aware kitchen memory. Unlike generic chatbot recall, Scraps maintains structured cooking data: what's in your fridge (with freshness tracking), who you cook for (with allergens, dietary restrictions, and preferences), your recipe collection (with cook notes and per-diner ratings), your shopping list, and your kitchen equipment. 27 tools across 6 domains let agents read kitchen context, suggest meals that respect dietary safety, update the pantry after cooking, and build a history of what works for your household. Every interaction makes the data richer. Cooking history, preference signals, kitchen awareness = better suggestions next time. All tools work via oAuth and a free scraps.kitchen account.
Family meal planning run by your agent: weekly dinners, household votes, grocery list minus pantry.
AI-powered kitchen management — pantry, recipes, meal plans, shopping lists
