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mrslbt

tabedata-mcp

by mrslbt

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
MCP_HTTP_HOSTNoHost for HTTP transport (default 127.0.0.1).127.0.0.1
MCP_HTTP_PORTNoPort for HTTP transport (default 8787).8787
MCP_TRANSPORTNoTransport type: stdio or http.stdio
MCP_AUTH_TOKENNoBearer token for HTTP transport. Required if MCP_TRANSPORT is http.
MCP_HTTP_ALLOWED_ORIGINSNoComma-separated CORS allowlist for HTTP transport.

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}
prompts
{
  "listChanged": true
}
resources
{
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
search_foodA

Search an AI-compiled 460-item Japanese food database by English or Japanese keyword (e.g. 'salad chicken' or 'サラダチキン'), returning macros, allergens, and a cited source per item. Sources are manufacturer labels, restaurant nutrition PDFs, Japan's MEXT food-composition database, or flagged estimates; each item carries a confidence level and a source URL to check the value against. Values are AI-compiled from those sources, not individually human-verified — treat them as a reference.

AIが編集した日本の食品データベース(460件)を日本語・英語のキーワードで検索し、各商品のマクロ栄養素・アレルゲン・出典を返します。出典はメーカー表示・飲食店の栄養PDF・文部科学省食品成分データベース・推定値のいずれかで、各商品に信頼度と確認用の出典URLが付きます。値はAIが各出典から編集したもので、人手による個別検証は行っていません。参考値としてご利用ください。

konbini_itemA

Look up konbini items (7-Eleven, Lawson, FamilyMart, Ministop) by chain. Most items are AI-compiled from official product labels; a small share are flagged estimates where label data was unavailable — each item returns its source URL, type, and confidence so you can check the value. Values are not individually human-verified; treat them as a reference.

コンビニ商品(セブン-イレブン・ローソン・ファミリーマート・ミニストップ)をチェーン別に検索します。多くは公式の商品表示からAIが編集していますが、一部は表示が入手できず推定値です。各商品に出典URL・種別・信頼度を付与しているため値を確認できます。人手による個別検証は行っていないため参考値としてご利用ください。

restaurant_mealA

Look up a restaurant chain meal with size variants, AI-compiled from official chain nutrition PDFs, allergen tables, and product labels — cited per item, with a small share flagged as estimates where official figures were unavailable. Values are not individually human-verified; treat them as a reference. Default size is 並 (regular); the modifications field is recorded but not yet applied to nutrition totals.

飲食チェーンのメニューをサイズ違いで検索します。各社公式の栄養PDF・アレルゲン表・商品表示をもとにAIが編集し、商品ごとに引用URLを保持(一部は公式値が入手できず推定値)。人手による個別検証は行っていないため参考値としてご利用ください。既定サイズは並。「玉子追加」などの変更項目は記録のみで、栄養への反映は未対応です。

analyze_mealA

PREFERRED tool whenever the user describes a whole meal (two or more items): resolves every item in ONE call and returns macro totals plus target comparison. Do NOT decompose a meal into separate konbini_item/restaurant_meal/search_food lookups. In clients that support MCP Apps it also renders a visual nutrition label. Recognizes counts ('2 eggs'), weights ('200g rice'), fractions ('half avocado', '3/4 portion'), and restaurant size names ('Nakau large oyakodon'). Optional user_profile compares totals against personalized targets (pass it whenever the user shares their stats).

自然言語の食事リストを解析し、PFC・繊維・ナトリウムの合計を返します。「2個」「200g」「半分」「3/4」「Nakau 大盛」など多様な指定に対応。user_profile を渡すと個別目標との差分も返します。

find_alternativesA

Find alternatives for a food along a chosen axis: higher protein, lower calorie, or lower sodium. Returns each alternative with its improvement and tradeoff.

ある食品の代替案を、たんぱく質・カロリー・ナトリウムなど指定軸で提案します。改善点とトレードオフを併記します。

daily_targetsA

Calculate personalized daily calorie, protein, carb, fat, fiber, and water targets. Uses Mifflin-St Jeor for BMR, an activity multiplier for TDEE, and a goal-driven deficit/surplus. Diabetes risk shifts the macro split toward fat (35%) to lower carb load. Hypertension surfaces a sodium guidance note.

個別の1日あたりカロリー・PFC・繊維・水分量を算出します。BMR は Mifflin-St Jeor、TDEE は活動係数、目標から赤字・黒字を決定。糖尿病リスクがある場合は脂質比率を高めて糖質負荷を抑えます。

Prompts

Interactive templates invoked by user choice

NameDescription
plan_my_dayCompute personalized daily targets, then plan and check a Japanese-friendly meal against them. 1日の目標を計算し、それに合わせた食事を提案・確認します。

Resources

Contextual data attached and managed by the client

NameDescription
Nutrition labelInteractive MCP Apps widget for analyze_meal.

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