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wangshunnn

bilibili MCP Server

by wangshunnn
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TypeScript
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose targeting different resources: user information, video information, and video search. There is no overlap in functionality, making tool selection straightforward for an agent.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern (get_user_info, get_video_info, search_videos) with clear, descriptive names that align well with their functions.

    Tool Count3/5

    With only 3 tools, the server feels thin for a Bilibili platform that likely has more capabilities (e.g., comments, playlists, subscriptions). While the tools cover basic operations, the count is borderline low for the domain's scope.

    Completeness2/5

    The toolset is severely incomplete for a Bilibili server, missing essential CRUD operations like creating or updating content, managing interactions (e.g., comments, likes), and accessing user-specific features (e.g., subscriptions, history). This will cause significant agent failures in broader workflows.

  • Average 2.9/5 across 3 of 3 tools scored.

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

    • 1 of 1 community issues answered or closed 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.

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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 carries the full burden of behavioral disclosure. It states the action ('Get information') but doesn't describe what information is returned, any rate limits, authentication needs, or error conditions. For a tool with no annotations, this leaves significant behavioral gaps, though it doesn't contradict any annotations.

    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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to understand at a glance. Every part of the sentence earns its place by conveying essential information.

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

    Completeness2/5

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

    Given the tool's simplicity (1 parameter, no output schema, no annotations), the description is minimal. It lacks details on what user information is returned, any usage constraints, or output format, which are important for a tool with no structured output documentation. This makes it incomplete for effective agent use beyond basic invocation.

    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% description coverage, with the 'mid' parameter clearly documented as 'User's numeric ID' with type and constraints. The description doesn't add any parameter-specific details beyond what the schema provides, such as examples or format explanations. With high schema coverage, the baseline score of 3 is appropriate as the schema handles the heavy lifting.

    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 verb ('Get') and resource ('information about a Bilibili user'), making the purpose understandable. It doesn't explicitly differentiate from sibling tools like 'get_video_info' or 'search_videos', which operate on different resources, but the distinction is implicit through the resource type. This is clear but lacks explicit sibling differentiation.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

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

    The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, context for usage, or comparisons to sibling tools like 'get_video_info' for video-related queries. Without such guidance, users must infer usage based on the tool name alone.

    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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Get' implies a read operation, it doesn't specify whether this requires authentication, has rate limits, returns paginated results, or what kind of detailed information is included (e.g., metadata, statistics, comments). This leaves significant gaps for agent decision-making.

    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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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

    Completeness2/5

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

    For a tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'detailed information' includes, the response format, or behavioral aspects like error handling. Given the complexity of video data and lack of structured output documentation, more context is needed for effective agent use.

    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 schema description coverage is 100%, with the single parameter 'bvid' clearly documented in the schema. The description doesn't add any parameter-specific details beyond what's in the schema, so it meets the baseline of 3 where the schema does the heavy lifting.

    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 verb ('Get') and resource ('detailed information about a Bilibili video'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its sibling 'search_videos', which might also return video information but with different parameters or scope.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

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

    The description provides no guidance on when to use this tool versus alternatives like 'search_videos'. It doesn't mention prerequisites (e.g., needing a BVID), exclusions, or contextual factors that would help an agent choose between sibling tools.

    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 are provided, so the description carries the full burden of behavioral disclosure. The description only states the basic purpose without mentioning any behavioral traits such as rate limits, authentication requirements, pagination behavior, or what the search results include (e.g., metadata fields). This leaves significant gaps for an AI agent to understand how to use it effectively.

    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 a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration.

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

    Completeness2/5

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

    Given the lack of annotations and output schema, the description is incomplete. It doesn't address key contextual aspects like what the search returns (e.g., list of video objects, error handling), behavioral constraints, or how it differs from sibling tools. For a search tool with no structured output information, more detail is needed.

    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% description coverage, with clear documentation for all three parameters (keyword, count, page). The description adds no additional meaning beyond what the schema provides, such as explaining search semantics (e.g., partial matches, relevance scoring) or parameter interactions. Baseline 3 is appropriate when the schema does the heavy lifting.

    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 ('Search for') and resource ('videos on Bilibili'), providing a specific verb+resource combination. However, it doesn't explicitly distinguish this tool from its sibling tools (get_user_info, get_video_info), which are likely for retrieving specific user or video details rather than performing searches.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

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

    The description provides no guidance on when to use this tool versus alternatives. It doesn't mention the sibling tools (get_user_info, get_video_info) or explain scenarios where searching for videos is appropriate compared to directly fetching known video or user information.

    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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