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jmanek

google-news-trends-mcp

by jmanek

get_news_by_keyword

Search Google News for articles matching a keyword, with adjustable date range, result count, and optional summaries.

Instructions

Find articles by keyword using Google News.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNoNumber of days to look back for articles.
keywordYesSearch term to find 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

C2.8/5.0
Behavior1/5

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 only states 'Find articles by keyword using Google News' with no mention of default behavior, pagination, rate limits, result ordering, or what happens with empty results. This is critically insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence, but it sacrifices completeness for brevity. It earns its place in terms of efficiency, but it lacks critical usage and behavioral information. A more informative but still concise description would be better.

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 5 parameters and an output schema, the description is far too minimal. It does not explain how to use the tool effectively (e.g., combining parameters, default values). The output schema reduces the need to describe return values, but the description still fails to provide adequate high-level context.

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% (all 5 parameters have descriptions), so baseline is 3. The description adds no additional parameter meaning beyond what the schema already provides. It does not mention any parameter constraints or defaults.

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 'Find articles by keyword using Google News' clearly states the specific verb (find), resource (articles), and method (by keyword). It distinguishes from sibling tools like get_news_by_location and get_news_by_topic through the keyword focus.

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 siblings (e.g., get_news_by_location, get_top_news). There is no mention of use cases, when not to use, or alternatives. The agent must infer from the name alone.

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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