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robbyczgw-cla

web-search-plus-mcp

Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v4.0.3

  • Disambiguation5/5

    The two tools have distinct purposes: web_search finds web content, while web_extract retrieves content from a specific URL. There is no overlap in their core actions.

    Naming Consistency5/5

    Both tool names follow the same web_verb pattern, with clear and predictable naming. The convention is consistent and readable.

    Tool Count3/5

    With only two tools, the server sits at the borderline of being too thin. The two tools are individually useful, but the small count suggests a narrow scope.

    Completeness4/5

    The server covers the two core operations one would expect for a web search and extraction service. Minor gaps like search result pagination or provider selection details exist but are not critical.

  • Average 3.3/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • 1 of 1 community issues answered or closed in the last 6 months
    • 38 commits in the last 12 weeks
    • Last stable release on
    • 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.

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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, and it does a solid job: it reveals that responses preserve bounded-context limits, include truncation warnings, retain evidence, and reference page-on-demand stored-content. These are genuinely useful behavioral traits an agent needs to anticipate before calling, going beyond a mere 'extracts pages' statement.

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

    Conciseness4/5

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

    The description is tight at two sentences, front-loading the core purpose before the behavioral notes. No filler or redundant phrasing, though the second sentence is dense with jargon (bounded-context limits, page-on-demand stored-content) that could be simplified.

    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?

    For a tool with 8 parameters, no annotations, and no output schema, the description is too thin. It explains provider-source behavior but omits guidance on key options like rendering JavaScript, image/raw-HTML inclusion, or the semantic-span selection feature. An agent cannot infer how renders_js or include_raw_html affect output from this text.

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

    Parameters2/5

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

    Schema description coverage is only 38% across 8 parameters, and eight parameters (spans, format, render_js, include_images, include_raw_html, spans_query, provider) receive no explanation in the description. The only link is the mention of '9 providers', which loosely maps to the provider enum, but the description does not compensate for the heavy schema gap.

    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 states a specific verb+resource pair ('source-only URL extraction' from URLs) and names the 9 providers behind it. 'Source-only' clearly implies the tool works from given URLs rather than search terms, which helps distinguish it from its only sibling web_search, though it never names that sibling explicitly.

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

    Usage Guidelines3/5

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

    'Source-only URL extraction' implies the tool is for extracting content from URLs you already have, and by contrast web_search would be for discovering URLs via queries. However, the description never explicitly states 'use this when you have URLs' or 'use web_search when you need to find pages', leaving the routing decision to inference.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations, the description must carry the burden of disclosing behavioral traits. It does mention that the tool returns 'additive v3 evidence, routing receipts, provider attempts, cache provenance, and typed errors,' which gives some insight into output complexity and routing behavior. However, it does not explicitly state that the operation is read-only, mention rate limits, or disclose any side effects. The mention of provider routing and receipts is useful but leaves room for more transparency.

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

    Conciseness4/5

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

    The description is a single, information-dense sentence. It front-loads the core purpose ('web search') and then lists unique output characteristics without wasting words. It is concise and well-structured, though it could be formatted as a short list to improve scannability. Overall, it earns its place.

    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?

    This is a complex tool with 14 parameters, 6 enums, and no output schema or annotations. The description is minimal and does not provide guidance on how to use key parameters like mode, depth, provider, or research_time_budget. It does not explain trade-offs among providers or when to enable research mode. While the schema describes each parameter's semantics, the tool-level description offers no context on overarching behavior, usage patterns, or limitations. For such a feature-rich tool, the description is insufficiently complete.

    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?

    All 14 parameters are described in the input schema (100% coverage), so the baseline is 3. The tool description adds no additional meaning about the parameters themselves; it only mentions 'routing across providers' and 'evidence,' which is already implied by the schema. Since every parameter is individually documented, the description does not need to compensate, but it also does not enrich beyond schema.

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

    Purpose5/5

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

    The description clearly states the primary function: 'Source-only web search through the Web Search Plus v3 runtime.' It names the verb (search) and resource (web), and the phrase 'source-only' distinguishes it from the sibling tool web_extract, which presumably extracts content from a given source. The description is specific and immediately recognizable.

    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 no guidance on when to use this tool versus web_extract. It does not state conditions like 'use for finding sources, use web_extract for reading a page' or explain when to prefer search over extraction. No exclusions or alternative recommendations are given, leaving the agent to infer usage from the name alone.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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