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LokerL

DouYuSearcher MCP Server

by LokerL
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: get_room retrieves detailed information for a specific room by ID, while search_rooms finds multiple rooms by keyword with summary information. There is no overlap in functionality or ambiguity about when to use each tool.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun naming pattern (get_room, search_rooms) using snake_case. The naming is predictable and follows the same convention throughout the tool set.

    Tool Count2/5

    With only 2 tools, this server feels underpowered for a comprehensive DouYu search/seamless experience. While the tools cover basic lookup and search, the domain suggests additional operations like filtering by category, trending rooms, or user profiles would be expected for a complete surface.

    Completeness2/5

    The tool surface is severely incomplete for a DouYu search domain. There are significant gaps: no ability to browse categories/partitions, get trending/hot rooms, filter search results, or access user/profile information. Agents will hit dead ends when trying to perform common exploration tasks beyond basic ID lookup and keyword search.

  • Average 4.2/5 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.

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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

  • Behavior3/5

    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 describes the return format (Markdown table with specific fields) and hints at output behavior (image tags for URLs), but does not cover error handling, rate limits, authentication needs, or data freshness. It adequately explains what the tool does but lacks operational details.

    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 well-structured with bilingual sections for Args and Returns, making it easy to parse. It is front-loaded with the core purpose and avoids unnecessary details. However, the bilingual duplication slightly reduces efficiency, though it remains concise overall.

    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?

    Given the tool's low complexity (1 parameter, no annotations, no output schema), the description is largely complete. It explains the purpose, parameter, and return format in detail. Minor gaps include lack of error handling or performance notes, but for a simple read operation, this is sufficient.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The schema description coverage is 0%, so the description must fully compensate. It provides clear semantics for the single parameter 'room_id,' including its type (int), purpose (DouYu room ID), and an example (71415), adding significant value beyond the bare schema. No other parameters exist, making this comprehensive.

    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 specific action ('get room information') and resource ('DouYu room'), distinguishing it from the sibling tool 'search_rooms' which likely searches for rooms rather than retrieving by ID. The bilingual format reinforces the purpose without redundancy.

    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 implies usage by specifying 'by room ID,' which differentiates it from the sibling 'search_rooms' (suggesting search-based retrieval). However, it lacks explicit guidance on when to use this tool versus alternatives or any prerequisites, such as valid ID ranges or error cases.

    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?

    No annotations are provided, so the description carries the full burden. It discloses the return format (a Markdown table with specific fields) and that it searches rooms, which is useful. However, it lacks details on behavioral traits like rate limits, authentication needs, or error handling, leaving gaps in transparency for a search operation.

    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 and front-loaded with the core purpose, followed by structured sections for args and returns. The bilingual repetition adds some redundancy, but each sentence earns its place by reinforcing clarity without unnecessary fluff.

    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?

    Given the tool's low complexity (1 parameter, no annotations, no output schema), the description is mostly complete: it explains the purpose, parameter, and return format. However, it lacks details on behavioral aspects like search limitations or result ordering, slightly reducing completeness for a search tool.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    With 0% schema description coverage, the description fully compensates by explaining the 'keyword' parameter in both Chinese and English, clarifying its purpose as a search query. This adds essential meaning beyond the minimal schema, making it highly effective for parameter understanding.

    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 specific action ('search for DouYu rooms by keyword') and resource ('DouYu rooms'), distinguishing it from the sibling tool 'get_room' which likely retrieves a specific room rather than searching. The bilingual format reinforces the purpose without redundancy.

    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 implies usage context by specifying 'by keyword,' suggesting this tool is for finding rooms based on search terms rather than direct lookup. However, it does not explicitly state when to use this versus 'get_room' or provide any exclusions or alternatives, keeping it at a 4.

    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 there are no obvious security issues.
  • Evaluate tool definition quality.

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