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Nafi-Jza

WebSearch MCP Server

by Nafi-Jza
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Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool serves a clearly distinct purpose: open_browser for manual interaction, scrape for content extraction, search for web search, and youtube_transcript for YouTube transcripts. No overlap.

    Naming Consistency3/5

    Naming is inconsistent: scrape and search are single verbs, open_browser follows verb_noun, while youtube_transcript uses noun_noun. This lack of a uniform pattern could confuse an agent.

    Tool Count5/5

    With 4 tools, the server is well-scoped. Each tool provides essential functionality for web research without unnecessary bloat.

    Completeness4/5

    The tool set covers core web search, scraping, and transcript extraction, but lacks features like image search or search history. Still, it handles common workflows effectively.

  • Average 3.4/5 across 4 of 4 tools scored. Lowest: 2.8/5.

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

    • No community issues in the last 6 months
    • 22 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 ISC License.

  • 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

  • Behavior1/5

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

    No annotations are provided, and the description fails to disclose any behavioral traits such as authentication requirements, availability of transcripts for all videos, or response format. This is a significant gap.

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

    Conciseness3/5

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

    The description is a single sentence, which is concise but under-specified. It lacks important details, so it does not fully earn 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?

    Given no output schema and no annotations, the description should include more context about what the tool returns, potential errors, or usage limits. It is incomplete.

    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?

    Schema coverage is 100%, and the description does not add new meaning beyond what the schema already provides for the two parameters. Baseline score is appropriate.

    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 'Extract the transcript from a YouTube video' uses a specific verb and resource, clearly distinguishing it from sibling tools like open_browser, scrape, and search.

    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?

    No guidance on when to use this tool versus alternatives like scrape or search. The description does not mention limitations or prerequisites.

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

  • 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. It only specifies the use of DuckDuckGo but fails to disclose rate limits, result format, error handling, or any behavioral traits beyond the engine.

    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, consisting of a single front-loaded sentence with no wasted words. Every word earns its place.

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

    Completeness3/5

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

    Given the tool's simplicity (one parameter, no output schema), the description is adequate but minimal. It does not specify the structure of search results, pagination, or limitations, leaving gaps in understanding what the tool returns.

    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?

    Schema coverage is 100%, so the schema already describes the single parameter. The description adds no additional meaning beyond what the schema provides, meeting the baseline.

    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 verb 'Search' and resource 'the web using DuckDuckGo.' It effectively distinguishes from sibling tools like open_browser, scrape, and youtube_transcript, which perform different functions.

    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?

    No guidance on when to use this tool versus alternatives. There is no mention of appropriate scenarios, prerequisites, or exclusions, leaving the agent without context for selection.

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

  • Behavior2/5

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

    Without annotations, the description bears full responsibility for behavioral disclosure. It fails to mention limitations such as handling of dynamic content, authentication, rate limits, or what 'main content' means. This lack of detail hampers informed selection.

    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?

    A single, front-loaded sentence conveys the tool's action and output efficiently. Every word serves a purpose, with no redundancy or extraneous information.

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

    Completeness3/5

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

    For a simple tool with one parameter and no output schema, the description is adequate but lacks details on return format, error handling, or limitations. It provides minimal completeness beyond the obvious.

    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?

    With 100% schema description coverage, the schema already documents the 'url' parameter thoroughly. The description doesn't add meaning beyond the schema's own description, so baseline 3 is appropriate.

    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 uses a specific verb 'Load and extract' with a clear resource 'webpage' and output format 'Markdown'. It effectively distinguishes from siblings like open_browser (for interactive browsing) and search (for searching), as scraping is uniquely for extracting content as Markdown.

    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 implies usage for converting webpages to Markdown but offers no explicit guidance on when to use this tool versus alternatives (e.g., open_browser for interactive access, search for searching). No when-not-to-use or prerequisites are mentioned.

    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?

    Discloses blocking nature (pauses server) and purpose, but lacks details on prerequisites (e.g., GUI environment), failure modes, or security implications. No annotations to supplement.

    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?

    Two short sentences, front-loaded with primary action and purpose. Every word earns its place; no repetition or fluff.

    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?

    Adequate for a simple tool with one optional param and no output schema. Could mention that it requires a graphical display environment, but overall complete enough for a competent agent.

    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?

    Schema coverage is 100% with exact same description as in schema. Tool description adds no extra meaning beyond what the schema provides for the single parameter, so baseline 3.

    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?

    Clearly states it opens a headed browser for manual CAPTCHAs or login, distinguishing it from sibling tools like scrape (automated). Verb+resource+use case explicit.

    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?

    Implies use when human intervention for CAPTCHAs or login is needed. Context is clear, but no explicit exclusions or alternative comparisons to siblings.

    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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