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Sacode

SearxNG MCP Server

by Sacode
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'web_search' has a clearly defined and distinct purpose.

    Naming Consistency5/5

    Since there is only one tool, naming consistency is inherently perfect. The tool name 'web_search' follows a clear verb_noun pattern and is descriptive.

    Tool Count2/5

    A single tool is too few for a server named 'SearxNG MCP Server', which suggests a broader search functionality. While web search is core, the scope feels thin without additional tools like image_search, news_search, or configuration options.

    Completeness2/5

    The tool surface is severely incomplete for a search server. It only covers basic web search, missing obvious functionalities such as image search, news search, or advanced search parameters that would be expected from a search engine integration.

  • Average 2.9/5 across 1 of 1 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
    • Last stable release on
    • 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.

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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 the full burden of behavioral disclosure. It mentions that results are returned in text or JSON format based on a parameter, which adds some context about output behavior. However, it fails to disclose critical traits such as whether this is a read-only operation, potential rate limits, authentication needs, error handling, or any side effects. For a search tool with zero annotation coverage, this is a significant gap in transparency.

    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 concise and well-structured, consisting of two sentences that efficiently convey the core functionality and output format options. It avoids unnecessary details and is front-loaded with the main purpose. However, it could be slightly more polished by integrating the format explanation more seamlessly, but overall it's efficient with zero waste.

    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 moderate complexity (6 parameters, 1 required) and the presence of an output schema (which reduces the need to describe return values in the description), the description is somewhat complete but has gaps. It covers the basic action and output format but lacks usage guidelines, behavioral context, and deeper parameter insights. With no annotations and only partial compensation in the description, it's adequate but not fully comprehensive for effective 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 schema description coverage is 100%, meaning all parameters are well-documented in the input schema itself. The description adds minimal value beyond the schema by briefly mentioning the result_format parameter's effect on output format. However, it doesn't provide additional semantic context, examples, or usage tips for parameters like categories or time_range. Given the high schema coverage, a baseline score of 3 is appropriate as the description doesn't compensate with extra insights.

    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 performs a web search using SearxNG and returns formatted results. It specifies the action ('perform a web search'), resource ('web'), and output format ('formatted results'), making the purpose explicit. However, it doesn't differentiate from siblings since there are none, so it doesn't reach the highest score of 5.

    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. It mentions the result_format parameter but doesn't explain when to choose text vs. JSON, nor does it discuss any prerequisites, limitations, or typical use cases. This lack of contextual guidance leaves the agent without direction on optimal usage.

    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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