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General Tools

toriigate.dev

Provides food search and nutrition information for Japanese foods.

1 endpoint2 known toolsFirst detected July 25, 2026Last detected July 25, 2026

ENDPOINT 1

https://toriigate.dev/mcp/food-db

No auth detected

MCP server metadata

Name
toriigate/food-db
Version
0.2.0
Capabilities
tools.listChanged

Known tools 2

search_food

Search Japanese foods by name (Japanese or romaji-free text).

Inferred read-only
get_nutrition

Get nutrition facts per 100g for a food ID returned by search_food.

Inferred read-only

CONNECT WITH APPROVAL

Client installation

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

[mcp_servers.toriigate-food-db]
url = "https://toriigate.dev/mcp/food-db"
enabled = true
Claude Code

.mcp.json

{
  "mcpServers": {
    "toriigate-food-db": {
      "type": "http",
      "url": "https://toriigate.dev/mcp/food-db"
    }
  }
}
Claude Desktop

Settings → Connectors → Add custom connector

Name: toriigate-food-db
Remote MCP URL: https://toriigate.dev/mcp/food-db

Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.

Cursor

.cursor/mcp.json

{
  "mcpServers": {
    "toriigate-food-db": {
      "url": "https://toriigate.dev/mcp/food-db"
    }
  }
}
Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code
{
  "servers": {
    "toriigate-food-db": {
      "type": "http",
      "url": "https://toriigate.dev/mcp/food-db"
    }
  }
}
Generic MCP

Client-specific MCP configuration

{
  "name": "toriigate-food-db",
  "transport": "streamable-http",
  "url": "https://toriigate.dev/mcp/food-db"
}
MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

TRUST AND VERIFICATION EVIDENCE

Loading Trust v2 evidence…

Checking the associated registrable domain. The BuiltWith key remains server-side.

Indexed

Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.