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tobioffice

SearXNG MCP Server

by tobioffice
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JavaScript
Remote

Server Quality Checklist

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

  • Latest release: v0.5.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: searxng_web_search performs web searches to find URLs, while web_url_read reads content from specific URLs. There is no overlap or ambiguity between searching for information and retrieving content from a known URL.

    Naming Consistency4/5

    Both tools use snake_case naming, which is consistent. However, the naming patterns differ slightly: searxng_web_search includes the server prefix and specifies the action (search), while web_url_read is more generic. This minor deviation prevents a perfect score.

    Tool Count2/5

    With only two tools, the server feels under-scoped for a web search and content retrieval domain. While the tools cover basic search and reading, there are likely missing operations such as filtering search results, handling pagination, or advanced URL processing, making the count too low for comprehensive functionality.

    Completeness2/5

    The tool set is severely incomplete for a web search server. It lacks essential operations like refining searches (e.g., by date, site, or type), managing search sessions, or handling errors and rate limits. Agents will face dead ends when trying to perform more complex web research tasks beyond basic search and URL reading.

  • Average 3.3/5 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.

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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?

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions reading content but fails to disclose critical traits like whether it handles authentication, rate limits, error conditions (e.g., invalid URLs), content types (e.g., HTML, text), or any side effects. This leaves significant gaps in understanding the tool's behavior.

    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 with two sentences that directly state the tool's function and usage, with no wasted words. However, it could be slightly more front-loaded by leading with the core purpose more explicitly, but overall it's efficient and well-structured.

    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 (a web content reader with no annotations and no output schema), the description is incomplete. It doesn't explain what the tool returns (e.g., raw HTML, parsed text), error handling, or limitations, which are crucial for an AI agent to use it correctly. The lack of output schema exacerbates this gap, making the description insufficient for full contextual understanding.

    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 input schema has 100% description coverage, with the 'url' parameter documented as 'URL'. The description adds no additional meaning beyond this, such as format requirements (e.g., must include http://) or examples. Given the high schema coverage, the baseline score of 3 is appropriate, as the schema does the heavy lifting without extra value from the description.

    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 ('Read') and resource ('content from an URL'), making it understandable. However, it doesn't explicitly distinguish this from its sibling tool 'searxng_web_search', which appears to be a search tool rather than a direct URL content reader, so it misses full sibling differentiation.

    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 provides implied usage guidance by stating 'Use this for further information retrieving to understand the content of each URL,' suggesting it's for post-search content analysis. However, it lacks explicit when-to-use vs. when-not-to-use instructions or named alternatives, such as clarifying if it's for web pages only or how it differs from the sibling search tool.

    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 full burden for behavioral disclosure. It mentions the tool is 'ideal for general queries' and 'broad information gathering' which gives some context about scope, but doesn't address important behavioral aspects like rate limits, authentication requirements, result format, pagination behavior, or error handling. For a search tool with no annotation coverage, this leaves significant gaps.

    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 sized with two sentences that each serve a clear purpose. The first sentence establishes the core functionality, while the second provides usage guidance. There's no wasted text, though it could be slightly more front-loaded with the most critical 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 search tool with 5 parameters, 100% schema coverage, but no annotations and no output schema, the description provides adequate basic context about when to use the tool. However, it doesn't compensate for the lack of output schema by describing result format or structure, and with no annotations, it should provide more behavioral context about the search operation's characteristics and limitations.

    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 5 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions 'general queries' which aligns with the 'query' parameter, but provides no additional semantic context about parameter usage or interactions. Baseline 3 is appropriate when schema does the heavy lifting.

    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 API, specifying the action ('performs a web search') and resource ('SearXNG API'). It distinguishes from the sibling tool 'web_url_read' by focusing on search rather than reading specific URLs. However, it doesn't explicitly contrast with the sibling beyond implicit differentiation.

    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 context for when to use this tool ('ideal for general queries, news, articles, and online content' and 'for broad information gathering, recent events, or when you need diverse web sources'). It gives positive guidance but doesn't explicitly state when NOT to use it or mention the sibling tool as an alternative for specific cases.

    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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