Skip to main content
Glama
WilliamQAQ0v0

hot-content-mcp

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v2.4.0

  • Disambiguation5/5

    Each tool has a clear, distinct purpose: fetching hot content, searching within it, and clearing cache for each platform (Baidu and Bilibili). No overlap or ambiguity between tools.

    Naming Consistency4/5

    Tool names follow a consistent verb_platform_object pattern (get/search/clear). Minor inconsistency: Baidu uses 'hot_search' while Bilibili uses 'hot' and 'videos', but this is understandable and does not cause confusion.

    Tool Count5/5

    Six tools is well-scoped for a hot-content aggregation server covering two platforms. Each tool has a specific purpose and the count feels appropriate, not excessive or thin.

    Completeness5/5

    The server covers the essential operations for a hot content service: retrieving hot items, searching, and cache management for both Baidu and Bilibili. There are no obvious missing features for the stated purpose.

  • Average 3.2/5 across 6 of 6 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.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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?

    There are no annotations provided, so the description carries the full burden of behavioral disclosure. It only says 'get data' and does not mention that results may be cached (despite the use_cache parameter), potential rate limits, network dependency, or what the response looks like. This is minimal disclosure beyond the obvious read 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 a single concise sentence that directly states the tool's purpose. It is not verbose and the content is front-loaded. However, it is somewhat under-specified for a tool with two parameters, but the conciseness itself is good.

    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?

    With no output schema and no annotations, the description should explain what data is returned, but it only says 'data' without any structure. It also omits behavior related to the count and cache parameters, and provides no alternative guidance. The description is adequate for the simplest use but incomplete for an agent to fully understand the tool's behavior.

    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 descriptions for both parameters (count and use_cache). The tool description adds no parameter information beyond what the schema already provides. Baseline 3 is appropriate because 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 '获取百度热搜榜数据' clearly states the verb (获取/get) and resource (百度热搜榜数据/Baidu hot search data). It distinguishes from get_bilibili_hot by specifying Baidu, but does not clarify how it differs from the sibling search_baidu_hot_search, so it lacks full 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 such as search_baidu_hot_search or the cache clearing tools. There is no mention of prerequisites, intended use cases, or exclusions. The tool name and schema hint at caching and count, but the description itself gives no usage context.

    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 full burden. It only states that the tool searches for entries matching a keyword, but does not disclose any behavioral traits such as result limits, ordering, data freshness, or whether it is read-only. The description adds minimal value beyond the tool's name.

    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, compact sentence that conveys the essential purpose. No wasted words; it is appropriately sized for a simple one-parameter tool.

    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?

    With no output schema and no annotations, the description should clarify what results look like or how they are ordered. It does not explain the return format, pagination, or how 'hot search' is defined. Given the simplicity of the tool, this is a minimal but incomplete description.

    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 description coverage is 100%, as the only parameter 'keyword' has a description ('搜索关键词'). The tool description adds no extra meaning beyond the schema, so a baseline of 3 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 uses a specific verb ('搜索' - search) and resource ('百度热搜' - Baidu hot search), with a clear scope: items containing a specific keyword. This distinguishes it from the sibling get_baidu_hot_search, though it does not explicitly name that alternative.

    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?

    No guidance is provided on when to use this tool versus alternatives like get_baidu_hot_search. The description does not state that this tool is for filtering a full list, nor does it mention any prerequisites or exclusions.

    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 present, the description carries the full burden of behavioral disclosure. It only states 'get hot video data' and does not mention caching behavior, return format, data freshness, or the fact that use_cache defaults to true.

    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 a single, front-loaded sentence with no redundant wording. It is concise but very brief, omitting behavioral context that other dimensions capture; still, it is not padded or unclear.

    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 no annotations, no output schema, and sibling tools for search and cache clearing, the description is incomplete. It leaves out caching semantics, what the returned data looks like, and how it differs from search_bilibili_videos.

    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 provides 100% description coverage for both parameters: count and use_cache. The tool description adds no parameter-level context beyond what the schema already explains, so the baseline score of 3 is appropriate.

    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 uses an explicit verb '获取' (get) and a specific resource 'B站热门视频数据' (Bilibili hot video data). This clearly distinguishes it from sibling tools such as get_baidu_hot_search (different platform) and search_bilibili_videos (search vs. hot rankings).

    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?

    No guidance is provided on when to use this tool versus alternatives. There is no mention that it retrieves a trending/hot list rather than search results, nor any relationship to clear_bilibili_cache or search_bilibili_videos.

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

  • Behavior1/5

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

    With no annotations provided, the description carries full burden for behavioral disclosure. It does not mention that clearing the cache is destructive, irreversible, or that it invalidates data for get_baidu_hot_search. The agent cannot infer side effects.

    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, concise sentence that immediately conveys the operation. Every word is informative, and there is no wasted text.

    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 simplicity of the tool, the description is minimal but does not explain why or when to clear the cache, nor what impact it has on other tools like get_baidu_hot_search. The lack of annotations and output schema makes this an incomplete context for an agent.

    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?

    The tool has zero parameters, so the schema already trivially covers everything. The description adds no parameter details, but none are needed. Baseline of 4 applies for zero-parameter tools.

    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 action ('清除' - clear) and the resource ('百度热搜数据缓存' - Baidu hot search data cache). It is specific and distinguishes itself from sibling tools like get_baidu_hot_search and clear_bilibili_cache.

    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, such as after stale data or before regenerating cache. No alternatives or exclusions are mentioned, leaving the agent without context for choosing between this and related cache clearing 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?

    With no annotations, the description must disclose behavioral traits. It only states 'clear cache' without detailing whether data is permanently deleted, whether user settings are affected, whether the action is reversible, or if any confirmation is required. This is a significant gap for a potentially destructive operation.

    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 concise sentence that directly communicates the tool's purpose without any redundant or filler content. It is perfectly sized for its trivial parameter structure.

    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 absence of annotations and an output schema, the description should compensate by explaining the implications of clearing the cache (e.g., data loss, scope, reversibility). It currently only states the action, which is insufficient for an agent to fully understand the consequences and safe usage of a destructive 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?

    The tool has zero parameters, so the input schema fully documents everything. The description correctly adds no parameter details, and the baseline score of 4 applies since there is nothing additional to explain.

    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 action (清除 = clear) and the target (B站视频数据缓存 = Bilibili video data cache), distinguishing it from sibling search and hot-list tools as well as the analogous clear_baidu_cache tool.

    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?

    No guidance is provided on when to use this tool versus alternatives like clear_baidu_cache, nor any prerequisites, situations where it should be avoided, or expected side effects. The description is purely functional without contextual usage advice.

    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 for behavioral disclosure. It only states the search function and criteria, but does not mention whether results are read-only, pagination, output format, or any constraints. This leaves significant behavioral ambiguity for an agent.

    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 short sentence that immediately conveys the tool's purpose and search criteria. There is no filler, redundant information, or unnecessary detail—every word earns its place.

    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?

    The tool is simple with one parameter and no output schema, but the description does not mention what the response contains (e.g., list of videos, metadata, sorting). Without annotations or an output schema, the lack of return information leaves the agent guessing about the result format, making it adequate but not complete.

    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?

    The schema defines 'keyword' only as '搜索关键词' (search keyword). The description adds that the keyword matches title or UP主 name, giving meaningful semantic context beyond the bare parameter description. This helps the agent understand how to construct the keyword value.

    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 '搜索B站视频(根据标题或UP主名称)' clearly states the action (search), the resource (Bilibili videos), and the specific scope (by title or UP主 name). This distinguishes it from siblings like get_bilibili_hot, which retrieves hot videos, making the purpose unambiguous.

    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 parenthetical '根据标题或UP主名称' provides clear context for when to use this tool—when searching by title or uploader name. However, it does not explicitly mention alternatives or scenarios to avoid, so it lacks the explicit exclusions that would earn a 5.

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

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

hot-content-mcp MCP server

Copy to your README.md:

Score Badge

hot-content-mcp MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/WilliamQAQ0v0/hot-content-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server