Resolve Japanese food names to nutrition facts. All 2,538 foods from Japan's official tables.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"dev-toriigate-food-db": {
"command": "<see-readme>",
"args": []
}
}
}Are you the author?
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Resolve Japanese food names to nutrition facts. All 2,538 foods from Japan's official tables.
No automated test available for this server. Check the GitHub README for setup instructions.
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Japanese data tools for AI agents.
Japan has a wealth of clean, public, factual data — food composition tables, corporate registries, laws, land prices. Almost none of it is usable by AI agents: no clean APIs, Japanese-only interfaces, Excel files behind web forms. Meanwhile, agents worldwide get asked to do Japanese tasks every day.
Torii Gate is the gateway: each dataset becomes a remote MCP server that any agent can discover, connect to, and call.
| Tool | Description | Endpoint |
|---|---|---|
| Japan Food DB | Resolve Japanese food names (fuzzy/colloquial forms included) to nutrition facts per 100g, based on the official Standard Tables of Food Composition in Japan. Covers foods USDA and Open Food Facts don't. | /mcp/food-db |
More tools are on the way — corporate registry lookup, invoice registration checks, subsidy search. The platform is manifest-driven: adding a tool is one directory and one registry line.
Add the remote server to your client (Claude Code example):
claude mcp add --transport http japan-food-db https://toriigate.dev/mcp/food-db
Then ask things like "「セブンのサラダチキン」的な鶏むね肉のカロリーは?" — the agent calls search_food / get_nutrition and gets factual data with sources attached.
No API key is needed for the free tier (rate-limited).
npm install
npm run dev # local dev server on :8787
npm run typecheck
Smoke test:
curl http://localhost:8787/llms.txt
curl -X POST http://localhost:8787/mcp/food-db \
-H 'Content-Type: application/json' \
-H 'Accept: application/json, text/event-stream' \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"search_food","arguments":{"query":"ごはん"}}}'
src/tools/<name>/ and declares its MCP tools, pricing, and data sources in a manifest. llms.txt and MCP Registry server.json records are generated from manifests — never hand-written.Full datasets are imported at deploy time and are not part of this repository.
This platform is built and operated almost entirely by AI agents — planning, code, registry publishing, monitoring, and weekly funnel reports — with a human in the loop only for publish/kill approvals and a budget review. It is an open experiment in whether an AI-operated business unit can find real agent-to-agent demand. Funnel numbers and decisions will be published as we go.