kitchenowl-mcp
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
kitchenowl-mcp
An MCP server for KitchenOwl, built with FastMCP. It lets AI assistants (Claude, or any MCP client) manage your shopping lists, recipes, meal plan, and shared expenses over KitchenOwl's REST API.
It runs as a standalone service with streamable HTTP transport — typically as a Docker container next to your KitchenOwl instance. It is independent of KitchenOwl's built-in /api/mcp endpoint and also works with older KitchenOwl servers.
Quick start (Docker Compose)
cp .env.example .env # fill in KITCHENOWL_TOKEN (and JWT_SECRET_KEY for the bundled KitchenOwl)
docker compose up -dThe MCP endpoint is then available at http://localhost:8000/mcp.
If you already run KitchenOwl elsewhere, only build/run the kitchenowl-mcp service and point KITCHENOWL_URL at your instance.
Configuration
Env var | Required | Default | Description |
| yes | — | Base URL of your KitchenOwl instance (no trailing |
| yes | — | Long-lived token of the KitchenOwl user to act as |
| no | auto | Default household; auto-picked when the user has exactly one |
| no |
| Where the MCP HTTP endpoint listens |
| no | unset | If set, MCP clients must send |
Getting a long-lived token
In the KitchenOwl app: Profile → Sessions → create a long-lived token, or via the API:
# 1. Log in (returns a short-lived access_token)
curl -X POST "$KITCHENOWL_URL/api/auth" -H 'Content-Type: application/json' \
-d '{"username":"you","password":"your-password"}'
# 2. Mint a long-lived token with it
curl -X POST "$KITCHENOWL_URL/api/auth/llt" \
-H "Authorization: Bearer <access_token>" \
-H 'Content-Type: application/json' -d '{"device":"kitchenowl-mcp"}'Related MCP server: lista-compras-mcp
Connecting a client
Claude Code:
claude mcp add --transport http kitchenowl http://localhost:8000/mcpClaude Desktop / claude.ai custom connector: add a remote MCP server with the URL
https://<your-host>/mcp(must be HTTPS-reachable; put a reverse proxy in front)MCP Inspector:
npx @modelcontextprotocol/inspector, connect tohttp://localhost:8000/mcp(streamable HTTP)
If MCP_SERVER_TOKEN is set, configure the client to send it as a bearer token.
Tools
All household-scoped tools take an optional household_id; with a single household (or KITCHENOWL_HOUSEHOLD_ID set) it can be omitted.
Households — list_households, get_household (includes member ids for expenses)
Shopping lists — list_shopping_lists, create_shopping_list, rename_shopping_list, delete_shopping_list, get_shopping_list_items, add_shopping_list_item, update_shopping_list_item, remove_shopping_list_items (batch), get_recent_items, get_suggested_items, add_recipe_items_to_shopping_list, search_items, update_item
KitchenOwl has no check/uncheck state: removing an item means it was purchased and feeds the purchase history and suggestions.
Recipes — list_recipes, search_recipes, get_recipe, create_recipe, update_recipe, delete_recipe, import_recipe_from_url (scrapes a recipe website; returns a draft unless save=true)
Meal planner — get_meal_plan, add_recipe_to_plan, remove_recipe_from_plan, get_recipe_suggestions
Expenses — list_expenses, add_expense, update_expense, delete_expense, get_expense_categories, create_expense_category, get_expense_overview
Security
By default the MCP endpoint is unauthenticated — anyone who can reach it acts as the configured KitchenOwl user. Options, in increasing order of robustness:
Keep the port on a trusted network (Docker-internal, LAN, VPN).
Set
MCP_SERVER_TOKENto require a bearer token (static token — fine for personal use, not a full auth system).Put a reverse proxy (Caddy/Traefik/nginx) with TLS in front — required anyway for claude.ai remote connectors.
Development
uv sync # install deps (Python >= 3.11)
uv run pytest # run the test suite (mocked KitchenOwl API)
uv run ruff check . # lint
KITCHENOWL_URL=... KITCHENOWL_TOKEN=... uv run kitchenowl-mcp # run locallyThe tests use FastMCP's in-memory client with a respx-mocked KitchenOwl API, so no running KitchenOwl instance is needed.
Limitations / roadmap
No item-catalog create/delete tools (
add_shopping_list_itemcreates catalog items implicitly).No household create/delete or member management.
Recipe
update_recipewithitems/tagsreplaces the full list (KitchenOwl API semantics).KitchenOwl's own experimental MCP endpoint (
/api/mcp, recent versions) is an alternative if you don't need a separately deployable server.
Tool Schema Changelog
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Maintenance
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AI-powered kitchen management — pantry, recipes, meal plans, 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.
Recipe search, ingredient matching, nutrition filters and a private cookbook for any AI agent.
Your kitchen in chat: pantry stock, shopping lists, recipes and scanned grocery receipts.
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