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youzhajun

Douyin Video Analysis MCP

by youzhajun
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v1.0.1

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion with other tools. The tool's purpose is clearly described and distinct by default.

    Naming Consistency5/5

    The single tool name 'analyze_douyin_video' follows a clear verb_noun pattern (analyze + video) with a platform prefix. There are no other tools to compare, but the name is consistent and descriptive.

    Tool Count3/5

    The server has only one tool, which feels thin for most use cases. While it may be sufficient for a narrowly focused analysis task, a typical well-scoped MCP server has 3-15 tools, making this borderline.

    Completeness4/5

    The single tool covers the primary operation of analyzing a Douyin video from a link. However, it lacks additional operations such as batch analysis or history retrieval, but for the stated purpose of analysis, it is reasonably complete.

  • Average 3.9/5 across 1 of 1 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • No commit activity data available
    • No stable releases found
    • 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.

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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?

    Without annotations, the description must disclose behavioral traits. It mentions automatic extraction and AI analysis but does not address potential limitations like rate limits, video length, or authentication requirements, leaving some behavioral 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 concise with two sentences, front-loading the main action and output. It is efficient and free of unnecessary words.

    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 no output schema, the description partially compensates by listing return fields (description, outline, tutorial steps). For a simple single-parameter tool, this is reasonably complete.

    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 already has 100% coverage with detailed description and examples. The tool description reiterates the parameter's purpose without adding new semantic info, so baseline score applies.

    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 tool analyzes Douyin video content, accepts links or codes, and returns structured analysis. It specifies the verb 'analyze' and resource 'Douyin video', and with no sibling tools, no differentiation needed.

    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 indicates when to use the tool (when a Douyin link or code is available) and explains the process. Since there are no sibling tools, it doesn't need alternative recommendations, but it lacks explicit 'when not to use' guidance.

    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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