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SecretRichGarden

Metaso Search MCP Server

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.1.2

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one performs searches across multiple scopes, and the other reads and converts a specific URL. There is no ambiguity between them.

    Naming Consistency5/5

    Both tools follow the same 'metaso_' prefix and use underscore-separated lowercase words. The naming pattern is consistent and predictable.

    Tool Count3/5

    With only two tools, the set is at the low end of acceptable. For a search-and-read server, the minimalism is defensible, but it feels slightly thin compared to a typical well-scoped server.

    Completeness4/5

    The search tool covers diverse scopes (web, documents, papers, images, videos, podcasts) and the reader handles URL content extraction. Together they cover the core search-and-read pipeline, though advanced features like search history or saved results are missing.

  • Average 3.7/5 across 2 of 2 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 Apache 2.0.

  • This repository includes a README.md 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

  • Behavior3/5

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

    There are no annotations, so the description carries the disclosure burden. It mentions optional behaviors like includeSummary, includeRawContent, and conciseSnippet, which is helpful, but these mostly restate schema information. It does not disclose limitations, rate limits, or result-format expectations.

    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 compact and well-structured with clear sections for scopes and features, front-loaded with a one-sentence summary. It avoids fluff, though the feature list overlaps with schema descriptions.

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

    Completeness4/5

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

    For a tool with six parameters and no output schema, the description covers all input options, scopes, and feature behaviors sufficiently for correct invocation. It lacks explicit output format details, but for a search tool the return type is reasonably inferred and no output schema is required.

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

    Parameters4/5

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

    Schema coverage is 100%, so the baseline is 3. The description adds value by explaining the meaning of each scope enum value and clarifying the effects of the boolean flags, which the schema's generic '搜索范围' description does not convey.

    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 it performs multi-dimensional search using Metaso AI, and enumerates supported scopes (webpage, document, paper, image, video, podcast). It distinguishes from the sibling metaso_reader by focusing on search, though it does not explicitly contrast with it.

    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?

    The description provides clear context about the available scopes and default behavior, which implies how to choose a search type. However, it offers no explicit guidance on when to use this tool instead of metaso_reader, nor any when-not-to-use or exclusion criteria.

    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?

    No annotations are provided, so the description carries the full burden. It discloses the core behavior (reads URL and converts format) and the output formats, which implies a read-only operation. However, it does not mention potential failure modes, restrictions (e.g., paywall, JavaScript-heavy pages), rate limits, or authentication needs. Since the tool seems simple and read-only, a 3 is appropriate—it adds some context but lacks depth.

    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 concise and well-structured: an initial statement, a bulleted list of formats, and a bulleted list of use cases. Every sentence adds value, with no redundant phrases. It is appropriately sized and easy to scan.

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

    Completeness4/5

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

    The tool is simple (2 params, no nested objects, no output schema), and the description covers purpose, formats, defaults, and use cases. It lacks explicit notes on error handling or limitations, but given the low complexity and clear schema, the description is largely complete. A 4 acknowledges minor missing behavioral context.

    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 already covers both parameters with descriptions and the enum for format; schema coverage is 100%. The description adds a list of supported output formats and default, but this largely duplicates the schema's 'default' field. The description does not provide additional meaning beyond the schema, so baseline 3 is fair.

    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 specifies that the tool reads a given URL's web content and converts it to structured formats (markdown/json). The verb '读取' and resource 'URL的网页内容' are specific, and the mention of structured output distinguishes it from a generic fetch tool. However, it does not explicitly contrast with the sibling tool 'metaso_search' (which likely searches), so it stops short of a 5.

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

    Usage Guidelines4/5

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

    The description lists concrete applicable scenarios such as extracting news articles, getting main body text, and converting pages to readable format. This provides clear context for when to use the tool. It does not explicitly exclude cases (e.g., 'do not use for search' or 'only for public pages'), but the scenarios are sufficient for basic guidance.

    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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