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juhemcp

Juhe News MCP Server

Official
by juhemcp
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Python
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one lists news by type, the other retrieves detailed content by ID. There is no overlap or ambiguity.

    Naming Consistency5/5

    Both tools follow a consistent snake_case pattern with the 'get_' prefix and a descriptive noun, making them predictable and easy to understand.

    Tool Count3/5

    With only two tools, the set is minimal for a news server. It covers basic listing and detail retrieval, but feels thin compared to typical news APIs that include search, categories, or pagination.

    Completeness2/5

    The tool surface lacks essential operations such as searching news, filtering by date or category, or pagination. Users cannot navigate beyond today's hot headlines, which is a significant gap for a comprehensive news service.

  • Average 3.4/5 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 status not available

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  • 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, and the description lacks details about behavioral traits such as read-only nature, authentication requirements, error handling, or response format. It only implies a read operation through the verb 'get'.

    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 extremely concise (one sentence) and directly conveys the core purpose. It is front-loaded and wastes no words, though it could include more context without sacrificing brevity.

    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 simple retrieval tool with one parameter and no output schema, the description is adequate but not complete. It does not specify the structure or scope of the detailed content, nor any edge cases like missing IDs.

    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% coverage with a clear description for the only parameter. The tool description adds no additional meaning beyond what the schema already provides, so baseline score is appropriate.

    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 action (获取/get) and resource (新闻详细内容/detailed news content) with a specific identifier (by news ID). It distinguishes from the sibling tool get_news_list, which likely returns a list, by specifying 'detailed content'.

    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 does not explicitly state when to use or not use this tool, but it indicates the prerequisite by mentioning the origin of the uniquekey (from get_news_list), providing implicit context for usage.

    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?

    No annotations provided; description does not disclose any behavioral traits beyond the input schema. No mention of rate limits, pagination behavior, or data freshness.

    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?

    Single sentence, no filler. Perfectly concise for its purpose.

    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?

    Description is sufficient for a simple list tool but lacks context about output format (e.g., returns news items with title and id). With no output schema, the description could be more helpful.

    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 covers 100% of parameters with descriptions. The tool description adds no additional meaning beyond what the schema already provides.

    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?

    Description clearly states the tool fetches today's hot news headlines (资源) filtered by news type (维度). The verb '获取' is specific. It distinguishes from sibling tool get_news_content, which likely retrieves full article content.

    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?

    Description implicitly indicates use for browsing headlines, but lacks explicit guidance on when to use this versus get_news_content. No exclusions or prerequisites are mentioned.

    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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