MCP server
Japan Restaurant Calories
dev.omikuji/calories
Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools
Nutrition facts for 24,000+ menu items of 100+ Japanese restaurant chains, with sources.
Working at last checkVerified publisher: omikuji.devAbout 1,366 tokens per request once connected4 tools
https://calories.omikuji.dev/mcp
At a glance
- Type
- MCP server
- Publisher
- omikuji.dev (verified by the MCP Registry)
- Status
- Working at last check
- Tools
- 4
- Token cost
- About 1,366 tokens per request
- Sets up in
- Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok
- Last checked
- 26 Oct 2026, 08:29 UTC
Connect it to your agent
Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.
Claude Code
claude mcp add --transport http calories https://calories.omikuji.dev/mcp
Claude Desktop
Settings → Connectors → Add custom connector, and paste the URL.
Codex (config.toml)
[mcp_servers.calories] url = "https://calories.omikuji.dev/mcp"
Gemini CLI
{"mcpServers":{"calories":{"httpUrl":"https://calories.omikuji.dev/mcp"}}}
Cursor
{"mcpServers":{"calories":{"url":"https://calories.omikuji.dev/mcp"}}}
VS Code
{"servers":{"calories":{"type":"http","url":"https://calories.omikuji.dev/mcp"}}}
Antigravity
agy mcp add calories https://calories.omikuji.dev/mcp
ChatGPT
Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.
OpenAI API (Responses tools)
{"type":"mcp","server_label":"calories","server_url":"https://calories.omikuji.dev/mcp","require_approval":"always"}
Grok (xAI API tools)
{"type":"mcp","server_label":"calories","server_url":"https://calories.omikuji.dev/mcp"}
Tools
list_chains~125 tokens
List the restaurant chains, stores and packaged-food makers covered (makers have type: packaged_food_maker), with item counts (current items only), which nutrients each chain publishes and when the data was fetched. query filters by chain name and also returns each chain's source document URL.request_missing~264 tokens
Tell the site operator that a restaurant chain or menu item is missing. Use only after search_menu / list_chains could not find it AND the user actually wanted it. One request per chain or item. Only the chain, item and note are stored (no personal information is needed or kept). Requests are countesearch_menu~805 tokens
Search menu items of Japanese restaurant chains and stores, and packaged foods of Japanese food makers, and get their nutrition facts. Queries that return no results are counted anonymously (the query text and chain only) to decide which chains to add. query matches item name, size, category, genresum_items~172 tokens
Add up nutrition for a set of items (a meal, a day) using ids from search_menu. Nutrients that some items do not publish are reported in incomplete, because their total is an underestimate.
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