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kassol

mcp-searxng

by kassol

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.1.0

  • Disambiguation5/5

    Each tool serves a distinct role: one performs web searches and the other reads specific URLs. There is no overlap in functionality, making them easy to distinguish.

    Naming Consistency2/5

    The naming pattern is inconsistent: one tool uses the 'searxng_' prefix while the other does not, and the action-object order differs (web_search vs url_read). This mixed convention could confuse an agent.

    Tool Count3/5

    With only 2 tools, the server feels minimal and is below the typical well-scoped range of 3-15. However, the two tools do cover a basic search-and-read workflow.

    Completeness4/5

    The pair covers the core search and content retrieval workflow, which is sufficient for basic information gathering. Minor gaps exist, such as no advanced search options, but these are not critical for a simple search server.

  • Average 3.8/5 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 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.

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    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

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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?

    The description states a read operation, consistent with the readOnlyHint annotation, and adds that it returns content from a URL. However, it provides no additional behavioral details beyond what annotations already imply, such as output format or handling of dynamic content.

    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 short and front-loaded with the core purpose. The second sentence is somewhat redundant and awkwardly phrased ('further information retrieving'), but it does add a usage hint without being verbose.

    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 has six parameters including section, readHeadings, and paragraphRange, the description only says 'Read the content' without explaining how output varies with these options. The schema describes parameters well, but the absence of an output schema and limited description leaves some ambiguity about return behavior.

    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 description coverage is 100%, so the schema already documents all six parameters. The description adds no parameter-specific meaning, keeping this at the baseline.

    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 reads content from a URL with a specific verb and resource. It is distinguishable from the sibling search tool, though it doesn't explicitly differentiate itself.

    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?

    'Use this for further information retrieving to understand the content of each URL' provides a clear intended use case as a follow-up to retrieving URLs. It lacks explicit exclusions or alternative guidance, but the sibling name makes the contrast evident.

    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?

    Annotations already declare readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds that it uses the SearXNG API but no further behavioral details like pagination, result limits, or output format. This is adequate but not rich, consistent with the caliber where annotations carry most load.

    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 two sentences, front-loaded with the core action and then followed by use cases. Every sentence earns its place, with zero wasted words or redundancy.

    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 the tool's moderate complexity (5 params, 2 enums) and lack of output schema, the description provides sufficient context for typical use cases, covering the intent and scope. It doesn't explain return values, but the readOnly hint and param names compensate. A small gap in behavioral details (e.g., pagination) prevents a 5.

    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 description coverage is 100%, so all 5 parameters (query, pageno, language, safesearch, time_range) are already documented in the schema with descriptions. The description adds no extra parameter meaning beyond what the schema provides, so the baseline of 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 clearly states the tool 'performs a web search using the SearXNG API', identifying both the action and resource. It distinguishes itself from the sibling web_url_read by focusing on broad queries rather than reading a specific URL, making it unambiguous.

    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 provides clear usage context: 'ideal for general queries, news, articles, and online content' and 'Use this for broad information gathering, recent events, or when you need diverse web sources.' It implies when to use but does not explicitly state when not to use it or mention alternatives beyond the sibling, which keeps it just under a 5.

    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 the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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