mealie-mcp

mealie-mcp

Docker-hosted MCP server for Mealie that enables AI agents to read cookbooks, extract recipes, translate them if needed, store them in Mealie, and verify the results.

Category
Visit Server

README

Mealie MCP Server

Docker-hosted MCP server for Mealie. It gives an AI agent the tools to read a cookbook (e.g. a PDF), extract the recipes (translating them if needed) and store them in Mealie — then verify its own work.

Built against Mealie API v3.19.2. Transport: SSE (http://localhost:8001/sse) — persistent container, no subprocess spawning.

It deliberately covers only the endpoints that serve the cookbook → Mealie workflow (recipes, organizers, foods, units) plus read endpoints for verification. The rest of the Mealie API is intentionally omitted.

Prerequisites

  • Docker (with Compose)
  • A reachable Mealie instance
  • A Mealie API token (or a username/password)

Generate an API token

In Mealie: avatar → Settings → API Tokens → Create (or /user/profile/api-tokens). Copy the token — it is shown only once.

Quick Start

git clone https://github.com/NigelVanHattum/mealie-mcp.git
cd mealie-mcp

# Configure credentials
mkdir -p ~/.config/mealie-mcp
cat > ~/.config/mealie-mcp/config.json << 'EOF'
{
  "base_url": "https://mealie.example.com",
  "api_token": "your-api-token-here",
  "verify_ssl": true
}
EOF

# Start the server
docker compose up -d

The server runs at http://localhost:8001. Verify:

curl http://localhost:8001/health
# {"status": "ok"}

Connect to Claude

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "mealie": {
      "url": "http://localhost:8001/sse"
    }
  }
}

Restart Claude Desktop, then try: "Check my Mealie connection" → it calls get_current_user.

Claude Code

claude mcp add mealie --url http://localhost:8001/sse

Configuration

Loaded in this order (first found wins):

Priority Method Details
1 Config file Mount /config/config.json via Docker volume
2 Environment vars MEALIE_BASE_URL, MEALIE_API_TOKEN, …
Variable Required Description
MEALIE_BASE_URL yes Base URL, no trailing slash, e.g. https://mealie.example.com
MEALIE_API_TOKEN yes Long-lived API token (sent as Authorization: Bearer)
MEALIE_VERIFY_SSL no false to skip TLS verification (default true)
SERVER_HOST / SERVER_PORT no Bind address / port (default 0.0.0.0:8000 in-container)

The server authenticates to Mealie with API keys only — there is no username/password path.

Exposure & security

The MCP API itself is unauthenticated: /sse, /messages/ and /health have no inbound auth. Anyone who can reach the port can call every tool — including create_recipe, overwrite_recipe and delete_recipe — using the server's Mealie API key.

So treat the server as a private backend: let Obot (or your MCP host) connect to it over localhost or a private/Docker network, and do not expose the port to the public internet. If it must traverse an untrusted network, put a reverse proxy with authentication in front of it. Transport is SSE; Streamable HTTP can be added if your host prefers it.

Recommended agent workflow

  1. get_current_user — confirm the token works and note the active group.
  2. list_recipes with search — check the recipe doesn't already exist.
  3. create_recipe — one call stores a full recipe. Translate fields to the target language (e.g. Dutch) before calling. Pass ingredients and instructions as plain strings; pass categories / tags / tools as names (they are created automatically if missing).
  4. get_recipe with the returned slug — verify the stored content.

create_recipe and update_recipe merge onto the recipe's current state, so they never wipe fields you didn't provide. When you want a clean re-import, use overwrite_recipe instead: it replaces all recipe content explicitly — every content field you omit is cleared (identity, settings and image are kept).

Tools Reference

Group Tools
App / verify get_server_info, get_current_user
Recipes list_recipes, get_recipe, create_recipe, update_recipe, overwrite_recipe, delete_recipe
Organizers list_categories, create_category, list_tags, create_tag, list_tools, create_tool
Foods list_foods, create_food
Units list_units, create_unit

create_recipe — key fields

name (required), description, ingredients (string[]), instructions (string[]), recipeYield, servings, prepTime, cookTime, totalTime, categories (string[]), tags (string[]), tools (string[]), nutrition (object), orgURL, extras (object).

Ingredients are stored as free text by default — ideal for cookbook imports. For structured ingredients, pass an object per line ({quantity, unit, food, note}) and manage foods / units with their tools.

Development

pip install -e ".[dev]"
pytest

# Build image locally (tests run in the build stage — build fails if tests fail)
docker build -t mealie-mcp .

docker compose up

API Reference

Interactive docs for your instance: https://<your-mealie>/docs · OpenAPI: https://<your-mealie>/openapi.json

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured