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988664li-star

DuckDuckGo MCP Server

by 988664li-star
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Python
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: 'fetch_content' retrieves and parses content from a specific webpage URL, while 'search' queries DuckDuckGo for results. There is no overlap in functionality, and an agent can easily differentiate between fetching known content and searching for unknown information.

    Naming Consistency5/5

    Both tool names follow a consistent verb-based pattern: 'fetch_content' and 'search'. They use snake_case uniformly, and the verbs ('fetch', 'search') are clear and appropriate for their actions, making the naming predictable and readable.

    Tool Count2/5

    With only 2 tools, the server feels under-scoped for a DuckDuckGo MCP server. While the tools cover basic web content fetching and search, the domain suggests potential for more operations (e.g., image search, news search, or advanced query parameters), making the count too low for the apparent scope.

    Completeness3/5

    The tools cover core functionalities of fetching web content and searching, but there are notable gaps. For a DuckDuckGo server, missing operations like image search, video search, or localized searches could limit agent capabilities, though basic workflows are supported.

  • Average 3/5 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 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 to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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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 full burden for behavioral disclosure. It states the tool fetches and parses content, implying network I/O and data processing, but doesn't mention error handling, rate limits, authentication needs, timeouts, or what 'parse' entails (e.g., HTML extraction, text cleaning). This leaves significant gaps for safe and effective use.

    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 appropriately brief and front-loaded with the core purpose in the first sentence. The Args section is structured but includes an extraneous 'ctx' parameter not in the schema, slightly reducing efficiency. Overall, it avoids unnecessary verbosity.

    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 (network operations, parsing), lack of annotations, no output schema, and incomplete parameter documentation (schema coverage 0% with a mismatched 'ctx' mention), the description is insufficient. It doesn't cover return values, error cases, or behavioral constraints needed for reliable agent use.

    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 description adds basic meaning for the 'url' parameter ('The webpage URL to fetch content from'), which is helpful since schema description coverage is 0%. However, it doesn't clarify format requirements (e.g., must be HTTP/HTTPS, encoding), and the 'ctx' parameter is mentioned in the description but absent from the input schema, creating confusion without additional context.

    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 a specific verb ('fetch and parse') and resource ('content from a webpage URL'), making it immediately understandable. However, it doesn't differentiate from its sibling tool 'search', which might have overlapping functionality for web content retrieval.

    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 is provided about when to use this tool versus the sibling 'search' tool. The description mentions what it does but offers no context about appropriate use cases, prerequisites, or alternatives, leaving the agent to guess about tool 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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. While it mentions 'return formatted results,' it doesn't describe what format those results take, whether there are rate limits, authentication requirements, or any side effects. The mention of 'ctx: MCP context for logging' in the description (but not in the schema) suggests logging behavior, but this isn't fully explained.

    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 appropriately concise with a clear purpose statement followed by parameter documentation. The structure is logical with the main functionality first. The only minor issue is the inclusion of 'ctx' parameter in the description that doesn't match the schema, which creates some confusion.

    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 search tool with 2 parameters, no annotations, and no output schema, the description provides basic functionality but lacks important context. It doesn't explain result format, error conditions, or how it differs from the sibling 'fetch_content' tool. The parameter documentation helps, but behavioral aspects remain underspecified.

    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?

    The description adds significant value beyond the input schema, which has 0% description coverage. It explains that 'query' is 'The search query string' and 'max_results' is 'Maximum number of results to return (default: 10)'. It also mentions 'ctx: MCP context for logging' which doesn't appear in the schema at all, though this parameter documentation is incomplete.

    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: 'Search DuckDuckGo and return formatted results.' It specifies the verb ('Search'), resource ('DuckDuckGo'), and outcome ('return formatted results'). However, it doesn't explicitly differentiate from its sibling tool 'fetch_content' which might have overlapping functionality.

    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 alternatives. There's no mention of when this search tool is appropriate versus 'fetch_content' or other potential search methods. The only contextual information is in the parameter documentation, not usage 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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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