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PXSR

MCP Smart Searcher

by PXSR
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v0.2.1

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one fetches content from a specific URL, the other performs web searches. There is no overlap or ambiguity.

    Naming Consistency5/5

    Both tool names follow a consistent verb_noun pattern (fetch_web_content, web_search) using snake_case, making them predictable and easy to understand.

    Tool Count3/5

    With only 2 tools, the server is minimal but covers the basic search-and-fetch workflow. It feels slightly thin for a server named 'Smart Searcher' as it lacks additional features like content summarization or multi-URL fetch.

    Completeness3/5

    The surface covers the core operations of searching and fetching web content, but there are notable gaps such as no tool to fetch search results directly or to handle multiple URLs. Agents may need to combine calls manually.

  • 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 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 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 must cover behavioral traits. It mentions 'any public URL' and optional filtering, but omits details on error handling, redirects, authentication, or rate limits. The transparency is basic.

    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 structured with a clear header, Args list, and Returns section. It is not overly long, though the prompt examples could be slightly trimmed. Overall, it is efficient.

    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?

    The description covers the basic inputs and output, but lacks details on error scenarios, maximum allowable characters, or non-HTTP content handling. With no annotations, more context would be beneficial for complete understanding.

    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?

    Schema coverage is 0%, requiring the description to add meaning. It does so by describing the URL as 'public HTTP/HTTPS URL,' the prompt as an optional filter with examples, and max_chars with its default. This adds significant value beyond the schema.

    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 'Fetch and extract text content from any public URL,' providing a specific verb and resource. It distinguishes from the sibling 'web_search' by focusing on fetching a known URL rather than searching for URLs.

    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 explains the prompt parameter and default max_chars, implying usage for targeted extraction. However, it does not explicitly contrast with the sibling 'web_search' or state when not to use this tool, leaving room for ambiguity.

    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?

    With no annotations provided, the description bears the full burden. It mentions simultaneous multi-engine searching and returns formatted results, but does not disclose rate limits, error handling for failed engines, or blocking behavior. Adequate but not comprehensive.

    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 brief and well-structured, starting with the main purpose and then listing parameters in a clear args format. Every sentence serves a purpose with no 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?

    The tool has an output schema (not shown but indicated), so the description does not need to detail return values. With three parameters and a fairly broad search function, the description adequately covers the essentials, though more details on result format would be beneficial.

    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 input schema has 0% description coverage, so the description must compensate. It clarifies that the query must be non-empty, lists the available engines (partially compensating for missing enums), and specifies the limit range (1-50). However, it does not explain the default behavior when 'engines' is null.

    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 verb 'search' and the resource 'web', and specifies the distinctive feature of using multiple search engines simultaneously. This differentiates it from the sibling tool 'fetch_web_content' which likely retrieves content from a single URL.

    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 implies usage for multi-engine web searches but does not explicitly state when to prefer this tool over the sibling or when not to use it. No exclusion criteria or alternative suggestions are provided.

    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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