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williamvd4

Web Search MCP Server

by williamvd4

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is singular and clear, so an agent cannot misselect between multiple options.

    Naming Consistency5/5

    A single tool inherently has perfect naming consistency, as there are no other tools to compare it against for patterns. The name 'search' is straightforward and appropriate for its function.

    Tool Count2/5

    One tool is too few for a server named 'Web Search MCP Server', which suggests a broader scope like searching, filtering, or managing search results. A single search tool feels thin and limits functionality, making it borderline inappropriate for the implied domain.

    Completeness2/5

    The tool surface is severely incomplete for web search functionality. It only provides a basic search tool, missing obvious operations like filtering results, getting details, saving searches, or handling pagination, which are common in search domains and could lead to agent failures in complex tasks.

  • Average 2.9/5 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
  • 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.

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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

  • Behavior2/5

    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 mentions 'no API key required,' which adds some context about authentication, but fails to describe other critical behaviors such as rate limits, response format, error handling, or any constraints beyond the input schema. This leaves significant gaps for an agent to understand how the tool behaves.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is extremely concise and front-loaded, consisting of a single sentence that directly states the tool's function and a key feature ('no API key required'). There is no wasted language, making it efficient and easy to parse for an agent.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool's complexity as a web search function with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits, response format, and operational constraints, which are crucial for an agent to use the tool effectively. The high schema coverage helps with inputs, but overall context is insufficient.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The input schema has 100% description coverage, clearly documenting both parameters ('query' and 'limit') with details like default values and constraints. The description does not add any additional meaning beyond what the schema provides, so it meets the baseline score of 3 for high schema coverage without compensating with extra insights.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool's purpose with specific verb ('search') and resource ('the web using Google'), making it immediately understandable. However, since there are no sibling tools mentioned, it cannot demonstrate differentiation from alternatives, which prevents a perfect score.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides minimal guidance by mentioning 'no API key required,' which implies ease of use but lacks explicit instructions on when to use this tool versus alternatives or any context about limitations. No sibling tools exist, so no comparison is possible, but the description still lacks usage context.

    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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Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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