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OEvortex

DuckDuckGo Search MCP

by OEvortex
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JavaScript
Remote

Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.4.0

  • Disambiguation5/5

    Only one tool exists, so there is no possibility of confusion between tools. The two modes are clearly described within the single tool.

    Naming Consistency5/5

    With a single tool named 'web-search', the naming is self-consistent and follows a clear verb-noun pattern.

    Tool Count2/5

    A search server with only one tool feels too thin for the domain. Typically, separate tools for different search types (web, images, news, etc.) would be expected.

    Completeness2/5

    The single tool covers web and AI search but misses common search categories like images, news, and video, leaving notable gaps for typical search use cases.

  • Average 4.2/5 across 1 of 1 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
    • 3 commits in the last 12 weeks
    • Last stable release on
    • 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.

  • Tools from this server were used 2 times in the last 30 days.

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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?

    Annotations already declare readOnlyHint=true, so the tool is inherently read-only. The description adds behavioral context: what each mode returns (titles/URLs/snippets vs. AI answer), default backends, and that mode can be chosen. No contradictions; description supplements annotations well.

    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—two short sentences. It is front-loaded with the primary action and uses line breaks for readability. Every phrase adds value; no wasted words.

    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?

    Given no output schema, the description adequately covers return types per mode. It mentions key parameters (mode, backend) but omits mentioning 'numResults' for web mode or 'iaskMode'/'detailLevel' for AI mode. However, since the schema provides full descriptions and the tool is simple, completeness is high but not perfect.

    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 baseline is 3. The description adds minimal parameter semantics beyond the schema, only noting the default value for 'backend'. It does not elaborate on 'numResults', 'iaskMode', or 'detailLevel', but the schema descriptions are already sufficient. Hence score 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?

    The description clearly states the tool's purpose: 'Search the web.' It distinguishes two modes with specific outputs: 'mode="web" for standard DuckDuckGo results (titles, URLs, snippets)' and 'mode="ai" for AI-generated answers'. This provides a specific verb (search) and resource (web), and differentiates the major modes effectively.

    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 explicitly tells when to use each mode: 'Use mode="web" for standard DuckDuckGo results' and 'Use mode="ai" for AI-generated answers'. It also provides guidance on backend selection for AI mode. With no sibling tools, no explicit when-not is necessary, but the guidance is clear and actionable.

    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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  • Evaluate tool definition quality.

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