Voice AI Website Analyzer MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
With only one tool, there is no possibility for confusion or overlap. The tool's purpose is singular and clear.
Naming Consistency5/5The single tool uses a clear verb_noun pattern ('analyze_website'), which is consistent and descriptive. With one tool, naming consistency is trivially maintained.
Tool Count3/5A single tool is on the lower end for a server claiming to be a 'website analyzer,' but it covers the core functionality of crawling and extracting business context. It feels thin but is arguably appropriate for a focused tool.
Completeness4/5The tool comprehensively analyzes a website by crawling key pages and extracting business details. Minor gaps might include handling of dynamic content or pagination, but the main workflow is covered.
Average 4.1/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits 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, the description carries the full burden. It discloses crawling behavior (homepage + up to 4 additional pages), extraction of text and business details, and output format. This provides good behavioral insight, though it doesn't mention potential issues like login walls 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, concise, and front-loaded with the primary action. Every sentence adds value—crawl scope, extracted details, and output summary. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single parameter, lack of output schema, and no siblings, the description is complete. It explains what the tool does, how it behaves (crawling strategy), and what it returns, covering all necessary contextual information for an agent.
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 already provides 100% coverage with a clear description of the 'url' parameter. The tool description adds no additional meaning beyond what the schema states, so the baseline score of 3 is appropriate.
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 action ('Fetches and analyzes a website') and the purpose ('to extract business context'), with specific details about crawling up to 5 pages and extracting content types. No siblings exist, so no differentiation needed.
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?
The description implies usage for analyzing websites to get business context, but provides no explicit guidance on when to use this tool versus alternatives. Since no sibling tools exist, the lack of alternatives is acceptable, but it doesn't address 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.
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