@greatnxy/web-search-mcp
Server Quality Checklist
Latest release: v0.0.0
- Disambiguation5/5
There is only one tool, so there is no possibility of confusion between tools. The purpose of the server is unambiguous.
Naming Consistency5/5The single tool name 'web_search' follows a clear verb_noun pattern, consistent and self-explanatory.
Tool Count3/5With only one tool, the server is minimal but might feel thin for broader search needs. However, for a focused web search purpose, it is acceptable.
Completeness5/5For a web search server, the single tool covers the essential functionality of searching the web. There are no obvious gaps for the stated purpose.
Average 4/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly explains the provider fallback behavior (Tavily first, Brave only under specific failure conditions), which is non-obvious and valuable. However, it does not detail output format, error handling, or rate limits, but the core behavioral nuance is covered.
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 a single sentence, front-loaded with the primary purpose ('Search the web.'), followed by a concise fallback explanation. Every word earns its place; no filler or redundancy.
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 tool's simplicity and the schema's complete parameter coverage, the description is adequate. It adds key provider behavior that is not inferable from the schema. The lack of an output schema is a minor gap, but for a web search tool the return type is intuitive. Overall, the description is sufficient for an agent to select and invoke the tool correctly.
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 input schema provides 100% coverage of parameter descriptions, so the baseline applies. The description does not add any additional parameter-level details, but relies on the schema to explain query, country, freshness, max_results, and domain restrictions.
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?
The description clearly states the verb and resource: 'Search the web.' It also adds specific provider fallback logic (Tavily then Brave), which distinguishes the tool's behavior. Though no siblings are present, the purpose is unambiguous and not a tautology.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the tool's name and description ('Search the web.'), but there is no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. The fallback note hints at availability conditions but does not provide direct usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
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- Evaluate tool definition quality.
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