China Hot Trending MCP

Query Hot Trending

query_hot_trending

查询各大平台实时热搜/热榜。platform可选weibo/zhihu/bilibili/baidu/toutiao/douyin/tieba/juejin/all(默认)，limit单平台条数1-50默认20。数据来自各平台公开接口，缓存5分钟。

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "query_hot_trending"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No	单平台返回条数，1-50，默认 20（all 模式忽略此参数）
`platform`	No	平台名，或 "all"（默认，返回全部平台各 top10）	all

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed7 schema fields changedNov 9, 2026

addedInput schema / additionalProperties
```
Added value: +false
```

addedInput schema / properties / limit / description

Added value: +"单平台返回条数，1-50，默认 20（all 模式忽略此参数）"

removedInput schema / properties / limit / title
```
Removed value: -"Limit"
```

addedInput schema / properties / platform / description

Added value: +"平台名，或 \"all\"（默认，返回全部平台各 top10）"

removedInput schema / properties / platform / title
```
Removed value: -"Platform"
```

removedInput schema / title

Removed value: -"query_hot_trendingArguments"

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "type": "object"
+}

First observedSep 6, 2026

TDQS

A3.7/5.0

Behavior4/5

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

With no annotations supplied, the description carries the full burden and does add real behavioral context: data comes from each platform's public interfaces and results are cached for 5 minutes, which tells an agent to expect possibly stale data. It stops short of describing failure modes, rate limits, or partial-platform failures, so it is not fully complete.

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?

Three short sentences, front-loaded with the purpose, then parameters, then data-source/caching caveats. Every sentence carries information, though the parameter sentence largely duplicates the schema.

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?

An output schema exists, so return values need not be explained, and the description covers purpose, platform scope, limits, and caching. What remains missing is guidance on behavior when a platform fails or when cached data is stale, which is minor for a simple two-parameter read tool.

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%, so both parameters are already documented in the schema, including the 1-50 range, the default of 20, and the note that 'all' ignores limit. The description restates the same facts without adding format or edge-case detail, so the baseline 3 applies.

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 opens with a specific verb and resource: querying real-time hot-search/trending lists across major platforms. It enumerates the supported platforms, so an agent knows exactly what domain the tool covers. It does not explicitly distinguish itself from the sibling list_platforms, which keeps it from a 5.

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?

Usage is implied rather than stated: the platform enumeration and the 'all' default tell an agent how to scope a query, but there is no explicit when-to-use or when-not-to-use guidance and no mention of the sibling list_platforms as an alternative for discovering platforms.

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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