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HughesCuit

Heventure Search MCP

by HughesCuit
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

83%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.6.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one searches the web, the other retrieves content from a specific URL. There is no overlap in functionality, and their descriptions make the differentiation explicit.

    Naming Consistency5/5

    Both tool names follow a consistent verb_noun pattern: 'web_search' and 'get_webpage_content'. The naming is clear, predictable, and uses underscores consistently.

    Tool Count4/5

    With only two tools, the server is minimal but well-scoped for a search-and-retrieve workflow. While more tools could be added (e.g., for advanced filtering or caching), the current count fits the server's stated purpose without being too thin.

    Completeness5/5

    The tool set covers the basic search workflow: find pages via web_search, then extract content via get_webpage_content. There are no obvious gaps for the intended use case of retrieving text from web pages.

  • Average 4.5/5 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
    • 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.

  • 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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  "$schema": "https://glama.ai/mcp/schemas/server.json",
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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

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations, but description discloses stripping of non-content elements, truncation to 2000 characters, and empty string on failure. Provides adequate behavioral insight.

    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?

    Five concise sentences front-load the purpose. No redundant information; every sentence adds value.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given low complexity and no output schema, description fully covers return behavior, truncation, and failure modes. No gaps.

    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 100% for the single URL parameter; description adds context about JavaScript-rendered content limitations, which enhances understanding beyond 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?

    Clearly states the tool extracts readable text from a URL, specifying it strips scripts/styles/navigation. Distinguishes from sibling 'web_search' by indicating usage after search.

    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?

    Explicitly describes when to use: after web_search when full text of a search result page is needed. Does not explicitly state when not to use, but context is clear.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations provided, so description carries full burden. Discloses automatic rate limiting and caching, concurrent querying for 'both', and that actual results may be fewer. Clearly indicates read-only behavior (no destructive actions).

    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?

    Concise paragraph (5 sentences) with front-loaded purpose. Every sentence contributes essential information: purpose, use cases, engine options, default behavior, result format, and automatic features.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Despite lack of output schema, description details result format (title, URL, snippet). Covers all three parameters, engine behaviors, caching/rate limiting, and result count caveats. No missing context for a search tool.

    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 already has 100% coverage, but description adds value by explaining default behavior ('both' queries DuckDuckGo and Bing concurrently), environment variable requirements for serpapi/tavily, and that higher max_results increases latency.

    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?

    Clearly states 'Search the web using multiple search engines' and specifies the resource (web) and action (search). Distinguishes from sibling tool 'get_webpage_content' by focusing on search rather than 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 Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Explicitly says 'Use this tool when you need to find current information, articles, or references from the internet.' Provides context for engine selection (free vs. API-based), though it doesn't explicitly state when not to use it.

    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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