Skip to main content
Glama
rui497

TrendRadar MCP Server

by rui497

find_related_news

Find news articles related to a given title. Specify date range, similarity threshold, and limit to retrieve relevant stories from today or historical data.

Instructions

查找与指定新闻标题相关的其他新闻(支持当天和历史数据)

Args: reference_title: 参考新闻标题(完整或部分) date_range: 日期范围(可选) - 不指定: 只查询今天的数据 - "today", "yesterday", "last_week", "last_month": 预设值 - {"start": "YYYY-MM-DD", "end": "YYYY-MM-DD"}: 自定义范围 threshold: 相似度阈值,0-1之间,默认0.5(越高匹配越严格) limit: 返回条数限制,默认50 include_url: 是否包含URL链接,默认False(节省token)

Returns: JSON格式的相关新闻列表,按相似度排序

Examples: - find_related_news(reference_title="特斯拉降价") - find_related_news(reference_title="AI突破", date_range="last_week")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
thresholdNo
date_rangeNo
include_urlNo
reference_titleYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries full behavioral burden. It explains that results are sorted by similarity, that `include_url` saves tokens, and how the date range works. It does not mention potential limitations like data freshness or rate limits, but the core behavior is transparent.

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 a one-line summary, Args section, Returns, and Examples. It is somewhat lengthy due to date_range details, but every part earns its place and the structure aids comprehension.

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 5 parameters and an output schema, the description covers functional semantics, parameter details, output format, and examples. It lacks edge cases or error handling, but it is sufficiently complete for an agent to use the tool correctly in most scenarios.

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?

Schema description coverage is 0%, so the description must compensate. It fully explains every parameter: `reference_title` (full/partial), `date_range` (with preset and custom formats), `threshold` (meaning and default), `limit`, and `include_url` (purpose and token-saving). This is exemplary parameter documentation.

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 tool finds news related to a specified title and supports current/historical data. It uses specific verbs and resources, but does not explicitly distinguish itself from siblings like `search_news` or `get_latest_news`.

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?

The description provides detailed parameter usage, date range formats, and examples, making it clear how to invoke the tool. However, it does not explicitly state when to use this tool instead of alternatives such as `search_news`, nor does it list exclusions.

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

Install Server

Other Tools

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/rui497/my-trendradar'

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