KIKARET
Server Details
Structured Japanese childcare facility data with source-backed facts for AI.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
4 toolsget_facilityARead-onlyInspect
Get one KIKARET facility by facility_id. Returns facility identity, official URL, and basic resolved knowledge such as prefecture, city, address, phone, and facility type.
| Name | Required | Description | Default |
|---|---|---|---|
| facility_id | Yes | Facility UUID returned by search_facilities |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so no contradiction exists. The description adds value beyond those hints by enumerating what the caller receives: identity, official URL, and resolved fields like prefecture, city, address, phone, and facility type.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single focused sentence conveys the tool's purpose and return payload with no filler. The key action is front-loaded and every clause adds useful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, single-parameter lookup with strong annotations, the description provides enough detail about returned values to guide an agent. It does not describe missing-ID or error behavior, and 'such as' leaves the return list slightly open-ended, so it is not fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents facility_id thoroughly with type, format, pattern, and a note that it is returned by search_facilities. The description only restates the parameter name without adding semantic detail, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action — 'Get one KIKARET facility by facility_id' — and names the resource clearly. It also lists the returned content, distinguishing it from search_facilities, which would return multiple facilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is for fetching a single facility when you already have an ID, and the schema parameter notes that facility_id comes from search_facilities. It does not explicitly contrast with get_facility_knowledge or state when not to use it, so it falls short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_facility_knowledgeARead-onlyInspect
Get resolved KIKARET knowledge for one facility. Use facility_id from search_facilities. Optionally request specific schema keys. If keys are omitted, all resolved knowledge is returned with source metadata.
| Name | Required | Description | Default |
|---|---|---|---|
| keys | No | Optional schema keys such as capacity_total, weekday_open_time, principal_name. Omit to return all resolved knowledge. | |
| facility_id | Yes | Facility UUID returned by search_facilities |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool read-only and non-destructive. The description adds a useful behavioral default: omitting keys returns all resolved knowledge with source metadata. It does not cover error or empty-result behavior, but this is a low-risk read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no filler; the core operation, parameter source, and default behavior are front-loaded. Every sentence adds information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only getter with full schema coverage, the description is sufficient to select and invoke the tool. It even states that results include source metadata, though it does not detail the exact response shape beyond that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and both facility_id and keys are documented in the schema. The description adds provenance for facility_id and restates the omit-to-return-all behavior, but no meaningful semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Get'), a distinct resource ('resolved KIKARET knowledge'), and scope ('one facility'). This is clearly separable from siblings like get_facility (facility record) and search_facilities (facility search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives a concrete provenance instruction: take facility_id from search_facilities, and explains the optional keys behavior. It does not explicitly say when to use this tool instead of get_facility, so it falls short of full alternative routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pingARead-onlyInspect
Check whether the KIKARET MCP server is available.
| Name | Required | Description | Default |
|---|---|---|---|
| message | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description aligns with those annotations by describing a read-only availability check, but it does not disclose the response format or what the optional 'message' parameter does.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that immediately states the tool's purpose without any filler or redundant detail. It is appropriately sized for a simple ping operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity health-check tool, the description plus annotations are nearly sufficient for an agent to invoke it correctly. The main gaps are the undocumented optional 'message' parameter and the absence of any output schema or return-value description, but these are minor for a ping tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one optional string parameter 'message' with no description and 0% schema description coverage. The tool description does not explain what this parameter means or how it affects the invocation, so an agent cannot know whether to supply it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('check') and a clear resource ('KIKARET MCP server availability'), making it obvious that this is a health-check or ping tool. This distinguishes it from the sibling facility-related tools without needing to inspect their schemas.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives or mention any exclusions. However, the phrasing implies it should be used to verify server availability, likely before other calls, which provides only implicit usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_facilitiesARead-onlyInspect
Search KIKARET for childcare facilities by facility name. Use this first when you do not know the facility_id. Returns facility IDs and basic location/contact information.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results. Default 10. | |
| query | Yes | Facility name or partial facility name, for example チェリッシュ北綾瀬 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds useful behavioral context by stating it performs name-based search and 'Returns facility IDs and basic location/contact information,' which is especially valuable given there is no output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted content. The core action is front-loaded, followed by usage guidance and return-value summary. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only search tool with full schema coverage and clear sibling context, the description covers what the tool does, when to use it, and what it returns. Nothing essential is missing for an agent to select and invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents both query and limit fully. The description adds the search-by-name framing but does not provide extra parameter meaning beyond what the input schema already contains.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: 'Search KIKARET for childcare facilities by facility name.' It also differentiates from siblings by saying 'Use this first when you do not know the facility_id,' which clearly positions it against get_facility.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides an explicit usage condition: 'Use this first when you do not know the facility_id.' It implies that a facility_id-based lookup is the alternative, but does not explicitly name the sibling tool or state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
4 tool updates
- First observed
get_facility - First observed
get_facility_knowledge - First observed
ping - First observed
search_facilities
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, then choose Claim with GitHub. An organization namespace such asio.github.acme/serveralso needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.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
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
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
No comments yet. Be the first to start the discussion!
Related MCP Connectors
Deep, obscure Japanese station, accessibility & hazard data for AI agents. English-first.
Japanese law, corporation & statistics data as MCP, normalized to English with source attribution.
Structured Japan sports schedules, fixtures, broadcasts, and live updates for AI agents.
Search Japanese hotels by 48 verified kid-friendly conditions, with sources and dates.
Related MCP Servers
- AlicenseAqualityDmaintenanceProvides access to Japanese corporate-led childcare regulations, laws, guidelines, and standards via MCP tools, enabling accurate retrieval of official documents to prevent AI hallucinations.820MIT
- AlicenseAqualityBmaintenanceSearch Japanese hotels by 48 verified kid-friendly conditions (baby beds, kids meals, family baths, etc.), with sources and verification dates. Covers 2,000+ hotels on kids-stay.com.4MIT
- FlicenseNot gradedqualityBmaintenanceEnables AI agents to answer questions about Japanese long-term care supply and demand, such as whether a municipality has enough special nursing homes, using public data.-
- AlicenseNot gradedqualityBmaintenanceEnables AI assistants to search Japanese government subsidies and grants, including archived closed calls and recurring application periods based on historical data.16MIT
Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
get_facility and get_facility_knowledge both return resolved knowledge for a single facility, so an agent could easily pick the wrong one when it needs basic identity versus full knowledge with source metadata. search_facilities and ping are clearly distinct.
All tool names follow a clear snake_case pattern with verb-like prefixes: get_facility, get_facility_knowledge, and search_facilities. ping is a standard health-check exception but does not disrupt the overall consistency.
Four tools are well-scoped for a read-only facility lookup and knowledge retrieval server. Search, two levels of detail retrieval, and a health check each serve a distinct purpose with no obvious redundancy.
The core workflow is covered: search by facility name, get basic facility information, and retrieve detailed resolved knowledge with source metadata. A minor gap is that search only works by facility name, with no location- or type-based discovery options.