Yahoo! Shopping MCP
Server Quality Checklist
Latest release: v0.9.0-preview.3
- Disambiguation5/5
With only one tool, there is no possibility of overlap or confusion. The tool's purpose is clearly defined as read-only product search.
Naming Consistency5/5The single tool name 'search_products' follows a clear verb_noun pattern, which is consistent even with only one tool.
Tool Count3/5One tool feels thin for a shopping MCP, but it is scoped to read-only search, making the count borderline rather than extreme.
Completeness4/5The tool covers the stated purpose of searching products, but lacks additional operations like retrieving detailed product information or browsing categories. Within its limited read-only scope, it is mostly complete.
Average 4.2/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 34 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
This server has been verified by its author.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and destructiveHint=false, but the description adds explicit exclusions: '購入、注文、アカウント変更は行いません' (does not purchase, order, or change accounts). This adds concrete behavioral context beyond the generic hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three short sentences, front-loaded with the core action, followed by the read-only clarification and the parameter requirement. Every sentence earns its place with no redundant or vague text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the rich schema (15 parameters, all described, plus output schema) and safety annotations, the description is adequate. It covers the primary usage constraint and read-only scope, while the schema handles the rest. Slightly reduced because it doesn't summarize other constraints, but they are present in the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with every parameter having a description. The tool description only repeats the query-or-jan_code requirement already present in the schema's allOf/anyOf and its overall description, adding no new semantic meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description states 'Yahoo!ショッピングの商品を検索します' (searches Yahoo! Shopping products), which is a specific verb+resource. It also explicitly says '読み取り専用' (read-only), distinguishing it from transaction tools. No siblings exist to differentiate, but this is clear and specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description advises 'queryまたはjan_codeのいずれかを指定してください' (specify either query or jan_code), giving clear parameter guidance. It also states it does not perform purchases, orders, or account changes, implicitly defining when not to use it. No alternatives exist, but the guidance is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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