Mirobody
Lab results to LOINC codes and UCUM units, symptoms and diagnoses to ICPC-3. Offline, no API key.
Description from the maker (original English)
MCP server for accessing Yazio user & nutrition data (unofficial)
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
YAZIO_USERNAME, YAZIO_PASSWORDValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"yazio": {
"command": "npx",
"args": [
"-y",
"yazio-mcp"
],
"env": {
"YAZIO_USERNAME": "your-value",
"YAZIO_PASSWORD": "your-value"
}
}
}
}Run this in your terminal
claude mcp add yazio --env YAZIO_USERNAME=your-value --env YAZIO_PASSWORD=your-value -- npx -y yazio-mcpFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"yazio": {
"command": "npx",
"args": [
"-y",
"yazio-mcp"
],
"env": {
"YAZIO_USERNAME": "your-value",
"YAZIO_PASSWORD": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"yazio": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"yazio-mcp"
],
"env": {
"YAZIO_USERNAME": "your-value",
"YAZIO_PASSWORD": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account fliptheweb, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
You need to fill in: YAZIO_USERNAME, YAZIO_PASSWORD
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.0.15) reached the registry 15 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Mirobody, FHIR MCP Server, Google Health MCP
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Lab results to LOINC codes and UCUM units, symptoms and diagnoses to ICPC-3. Offline, no API key.
MCP server providing seamless access to FHIR APIs for AI tools and healthcare applications
Privacy-first unofficial Google Health API v4 MCP server for health, sleep, activity, HR agents
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
[!IMPORTANT]
This is not an official MCP server and Yazio does not provide an official API.
An MCP (Model Context Protocol) server that connects Claude/Cursor to your Yazio nutrition data. Track your diet, search food products, and manage your nutrition goals directly from your AI assistant.
Available on NPM: npx yazio-mcp
Claude Desktop Extension: ~~yazio-mcp.mcpb~~ — one-click install is broken upstream, see workaround.
Add the following JSON your MCP client configuration:
{
"mcpServers": { "yazio": { "command": "npx", "args": ["-y", "yazio-mcp"], "env": { "YAZIO_USERNAME": "your_email@emai.com", "YAZIO_PASSWORD": "your_password" } } } }
[!WARNING]
One-click
.mcpbinstall is broken by a Claude Desktop bug (mcpb#281). Workaround: download yazio-mcp.zip, extract it, and use Settings → Extensions → Advanced settings → Install Unpacked Extension. Or just use thenpxconfig above.
~/Library/Application Support/Claude/claude_desktop_config.json
claude mcp add yazio -e YAZIO_USERNAME=your_email@email.com -e YAZIO_PASSWORD=your_password -- npx -y yazio-mcp
Verify with claude mcp list.
There are a few ways to add the server:
Settings → MCP → + Add new MCP server, then fill in the command, args, and env.cursor/mcp.json in your project root~/.cursor/mcp.json (applies to all projects)*"Get my nutrition data for the last week and analyze my eating patterns"*
Claude can retrieve your daily summaries, identify trends, and provide insights about your eating habits, macro distribution, and areas for improvement.
*"Search for 'chicken breast' in the Yazio database"*
Find detailed nutritional information for any food product, including calories, macros, vitamins, and minerals.
*"Add 200g of grilled salmon for yesterday's dinner"*
Easily log meals you forgot to track in the Yazio app directly from Claude or Cursor.
| Tool | Description | Key Parameters |
|---|---|---|
get_user | Get user profile | - |
get_user_daily_summary | Get daily nutrition summary | date |
get_user_consumed_items | Get food entries for a date | date |
get_user_weight | Get weight data | date (optional) |
get_user_exercises | Get exercise data | date |
get_user_water_intake | Get water intake | date |
get_user_goals | Get nutrition goals | date (optional) |
get_user_settings | Get user preferences | - |
get_user_dietary_preferences | Get dietary preferences | - |
get_user_suggested_products | Get suggested products for a meal | date, daytime, limit (all optional) |
search_products | Search food database | query |
get_product | Get detailed product info | id |
get_recipe | Get a recipe with ingredients and nutrients | id |
get_user_recipes | Get your own recipes | - |
delete_user_recipe | Delete one of your own recipes | id |
add_user_consumed_item | Add food to your log | product_id, amount, date, daytime |
add_user_water_intake | Add water intake entry (cumulative value in ml) | date, water_intake |
remove_user_consumed_item | Remove food from log | itemId |
create_product | Create a custom product from label values per 100 g/ml | name, category, energy_per_100, protein_per_100, fat_per_100, carb_per_100 |
add_quick_entry | Log a one-off entry with total nutrition, without a product ("quick add") | name, date, daytime, energy |
add_user_consumed_recipe | Log portions of a recipe | recipe_id, portion_count, date, daytime |
YAZIO_USERNAME='your_email' YAZIO_PASSWORD='your_password' npx yazio-mcp
YAZIO_USERNAME=X YAZIO_PASSWORD=X npx -y @modelcontextprotocol/inspector npx <local-path>/yazio-mcp
MIT License - see LICENSE file for details.