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jmanek

google-news-trends-mcp

by jmanek

get_news_by_topic

Retrieve news articles by selecting a topic such as Technology, Health, or World. Filter by time period, get full data or summaries, and control the number of results for streamlined news discovery.

Instructions

Find articles by topic using Google News. topic is one of WORLD, NATION, BUSINESS, TECHNOLOGY, ENTERTAINMENT, SPORTS, SCIENCE, HEALTH, POLITICS, CELEBRITIES, TV, MUSIC, MOVIES, THEATER, SOCCER, CYCLING, MOTOR SPORTS, TENNIS, COMBAT SPORTS, BASKETBALL, BASEBALL, FOOTBALL, SPORTS BETTING, WATER SPORTS, HOCKEY, GOLF, CRICKET, RUGBY, ECONOMY, PERSONAL FINANCE, FINANCE, DIGITAL CURRENCIES, MOBILE, ENERGY, GAMING, INTERNET SECURITY, GADGETS, VIRTUAL REALITY, ROBOTICS, NUTRITION, PUBLIC HEALTH, MENTAL HEALTH, MEDICINE, SPACE, WILDLIFE, ENVIRONMENT, NEUROSCIENCE, PHYSICS, GEOLOGY, PALEONTOLOGY, SOCIAL SCIENCES, EDUCATION, JOBS, ONLINE EDUCATION, HIGHER EDUCATION, VEHICLES, ARTS-DESIGN, BEAUTY, FOOD, TRAVEL, SHOPPING, HOME, OUTDOORS, FASHION.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYesTopic to search for articles.
periodNoNumber of days to look back for articles.
full_dataNoReturn full data for each article. If False a summary should be created by setting the summarize flag
summarizeNoGenerate a summary of the article, will first try LLM Sampling but if unavailable will use nlp
max_resultsNoMaximum number of results to return.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A3.5/5.0
Behavior2/5

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

No annotations provided, so description carries full burden. It states articles are found via Google News but does not disclose behavioral traits such as rate limits, pagination, response format, or how parameters like full_data and summarize affect results. The description is too minimal to inform safe and effective invocation.

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?

Two-line description with no fluff: first line states purpose, second line lists topic options. Efficient and front-loaded. Every sentence serves a purpose.

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?

Given 5 parameters, an output schema, and no annotations, the description is adequate but not comprehensive. It explains the topic parameter well but offers no guidance on interpreting period, full_data, summarize, or max_results behavior. The output schema likely covers return format, so overall completeness is moderate.

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?

Schema description coverage is 100%, baseline 3. Description adds significant value for the topic parameter by enumerating 50+ valid values from the underlying source (Google News categories), which the schema only vaguely describes as 'Topic to search for articles.' This extra context helps the agent select correct inputs beyond what the schema provides.

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?

Description clearly states 'Find articles by topic using Google News' with a specific verb (Find), resource (articles by topic), and source (Google News). The list of valid topic values further clarifies scope and distinguishes from sibling tools like get_news_by_keyword, get_news_by_location, etc.

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 explicit guidance on when to use this tool versus alternatives. Does not mention when not to use it, prerequisites, or preferred scenarios compared to siblings like get_news_by_keyword or get_top_news. The description only lists topics, leaving the agent to infer usage context.

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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