uratori（ウラトリ）
Server Details
日本企業の第三者認証(ISO 27001/Pマーク/ISMAP等)を公開情報から実調査し、5区分の判定と証跡URLを返す。未確認は未取得の断定ではない。
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4.7/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: one provides definitions and context for interpreting results, the other performs the actual research. There is no overlap or ambiguity between them.
Both tool names follow a consistent verb_noun pattern using snake_case ('get_status_definitions', 'research_vendor_certifications'), making them predictable and easy to understand.
With only two tools, the server is at the lower end of the expected range. While the tools cover the core functionality, the small count may feel thin for broader use cases, but it is not extreme.
The server provides the essential research functionality and includes a definitions tool to interpret results. Minor gaps exist, such as lacking a way to compare multiple vendors or clear cached data, but the core workflow is well-covered.
Available Tools
2 toolsget_status_definitionsAInspect
uratori の判定5区分(verified_official / public_evidence / vendor_confirm_required / not_found / expired_or_negative)と、not_found の内訳4区分の定義、調査方法と限界を返す。research_vendor_certifications の結果を解釈する前に一度読むことを推奨。
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully relies on text. It clearly indicates the tool returns definitions and limits, implying a read-only operation. It could explicitly state 'read-only' or 'no side effects,' but the description is sufficient for understanding its non-destructive behavior.
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, information-dense sentence that lists categories, what is returned, and a usage recommendation. No wasted words, though it could be slightly restructured for readability. It earns its space.
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?
Given no parameters, no output schema, and a simple task of returning definitions, the description covers what the tool does, what it returns, and how to use it relative to the sibling. Completely adequate for an AI agent to understand and invoke it correctly.
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 tool has no parameters (input schema empty). Schema description coverage is effectively 100% since no parameters exist. The description adds no parameter info, but none is needed. Baseline 4 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 clearly states that the tool returns definitions, investigation methods, and limitations for the judgment categories (5 main and 4 subcategories). It also explicitly recommends reading this before using the sibling tool research_vendor_certifications, distinguishing its purpose.
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 provides explicit guidance: read this tool's output before interpreting results from research_vendor_certifications. This clarifies when to use it, and no alternatives are needed because there is only one sibling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
research_vendor_certificationsAInspect
日本の取引先(ベンダー)1社の第三者認証・監査レポート(ISO/IEC 27001, プライバシーマーク, ISMAP, SOC 2 等)の取得状況を、公開情報(公的レジストリ・企業公式サイト)から実調査して返す。判定は5区分(公式確認/公開記載=自己申告/要ベンダー確認/公開情報では未確認/失効・取消)で、各判定に証跡URLと取得日が付く。「未確認」は未取得の断定ではない。結果は参考情報であり、安全/危険の判定や認証の保証ではない。法人番号(13桁)を指定すると同名別法人との取り違えを防げる。無料・数十秒かかることがある。
| Name | Required | Description | Default |
|---|---|---|---|
| serviceUrl | Yes | 対象サービスまたは会社公式サイトのURL(http(s)) | |
| companyName | Yes | 会社名(例: フリー株式会社)。正式な登記名称に近いほど正確 | |
| serviceName | No | サービス名(任意。省略時は会社名を使用) | |
| corporateNumber | No | 法人番号13桁(任意・推奨。同名別法人の取り違え防止) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully carries the burden, disclosing that the tool may take tens of seconds, is free, and explaining the judgment categories and their interpretations (e.g., '未確認' is not denial of certification).
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 paragraph of approximately 200 characters, front-loaded with the main purpose, with every sentence adding necessary information and no redundancy.
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?
Despite no output schema, the description explains the output structure (5 judgment categories with evidence URLs and dates) and limitations (results are reference only). The tool has 4 parameters and moderate complexity, and the description covers all essential aspects.
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 baseline is 3. The description adds meaningful context for parameters: companyName (accurate name improves results), corporateNumber (prevents mix-ups), serviceUrl (target URL), and serviceName (optional but useful).
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 clearly states the verb (research/investigate) and resource (third-party certifications of a vendor), and distinguishes from the sibling get_status_definitions tool.
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 indicates when to use (to research certifications of a specific vendor) and provides guidance on optional parameters like corporateNumber to avoid confusion. However, it does not explicitly state when not to use or mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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
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!