A
licenseA
qualityA
maintenanceMCP server for Japanese food nutrition data, enabling bilingual JP/EN lookups across konbini, restaurant chains, and grocery brands.
6
61
2
MIT
Japan Food DB
Server Details
Resolve Japanese food names to nutrition facts. All 2,538 foods from Japan's official tables.
If you are the author of this connector, you can claim ownership with GitHub, an HTTP challenge, or a DNS record. Claimed connector authors can inspect health checks, view analytics, and manage their listing.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- yuki00yossi/toriigate-platform
- GitHub Stars
- 0
- Server Listing
- Japan Food DB
Available Tools
2 toolsget_nutritionGet nutrition facts by food IDAInspect
Get nutrition facts per 100g for a food ID returned by search_food.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Food ID from search_food, e.g. "chicken-breast" |
TDQS
A4/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It states the tool gets nutrition facts per 100g, which is adequate for a simple retrieval, but does not mention potential errors, authentication, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words, achieving high efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description covers the unit (per 100g) and source of ID, but omits details on the structure of returned data.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The sole parameter 'id' is described in the schema with an example. Schema coverage is 100%, so the description adds minimal value beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb (get), the resource (nutrition facts per 100g), and the input requirement (food ID from search_food), distinguishing it from the sibling search_food.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage after search_food and with a specific food ID. It does not explicitly exclude alternatives, but the context is clear given only one sibling exists.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_foodSearch Japanese foodsAInspect
Search Japanese foods by name (Japanese or romaji-free text). Returns candidates with nutrition per 100g, source, and disclaimer.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (default 5) | |
| query | Yes | Food name in Japanese, e.g. "鶏むね肉" or "ごはん" |
TDQS
A3.5/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that results include 'nutrition per 100g, source, and disclaimer', which is helpful. However, it does not describe response structure, pagination, or any other behavioral traits, leaving gaps for the agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with purpose, followed by output details. Every sentence is informative and there is no unnecessary text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the description covers the main purpose and output highlights. However, without an output schema, more detail on the return format would be beneficial. The sibling relationship is not addressed, slightly reducing completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. The tool description adds minimal value beyond confirming the 'query' parameter accepts Japanese or romaji text, which is already implied by the schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool searches Japanese foods by name, specifying the verb 'search' and resource 'Japanese foods'. However, it does not differentiate from the sibling 'get_nutrition', missing the chance to clarify when to use this tool vs the alternative.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for searching foods by name but provides no explicit guidance on when to use this tool vs alternatives, nor any exclusions or prerequisites. The sibling 'get_nutrition' is present but not mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Frequently Asked Questions
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as
io.github.alice/server, link the matching GitHub user or an account that owns the GitHub organization, then choose Claim with GitHub.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
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For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
Discussions
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Try in Browser
Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
A3.8/5.0
Disambiguation5/5
The two tools have clearly distinct purposes: one for searching foods by name, the other for retrieving detailed nutrition facts for a specific food ID. No overlap or ambiguity.
Naming Consistency5/5
Both tools follow a consistent verb_noun pattern: search_food and get_nutrition. The naming is predictable and clear.
Tool Count3/5
With only two tools, the server feels minimal for a food database. While it may serve a basic query need, the thin toolset borders on inadequate for broader use.
Completeness3/5
The domain is querying Japanese food nutrition, but search_food already returns nutrition per 100g, making get_nutrition potentially redundant. Missing features like category filtering or recipe lookup are notable gaps.