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Glama

Mediastack

by io.github.pipeworx-io

Search News

search_news
Read-onlyIdempotent

Search news articles by keywords. Optionally filter by category (business, technology, science, health, sports, entertainment, general), country (ISO2 codes), or language. Returns headlines, descriptions, sources, and published dates.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return (1-100, default 25)
_apiKeyYesMediastack API key
keywordsYesSearch keywords (e.g., "artificial intelligence", "climate summit")
countriesNoComma-separated ISO2 country codes (e.g., "us,gb,de")
languagesNoComma-separated language codes (e.g., "en,es,fr")
categoriesNoComma-separated categories: business, technology, science, health, sports, entertainment, general

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYesNumber of articles returned in this response
totalYesTotal number of matching articles available
articlesYesList of news articles matching the search criteria

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive). The description adds return value composition (headlines, descriptions, sources, dates) beyond annotations, providing useful behavioral context.

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 sentences, front-loaded with the primary action, no extraneous words. Every sentence adds value.

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?

For a search tool with output schema, the description covers key inputs and outputs. Lacks mention of pagination or sorting, but overall adequate given schema richness.

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 baseline is 3. The description restates filter options and categories but adds minimal new meaning beyond what the schema's parameter descriptions already provide.

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 tool searches news articles by keywords, with a specific verb and resource. It distinguishes from sibling 'latest_news' by emphasizing keyword-based search and optional filters.

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 description explains when to use (search with keywords and optional filters) but does not explicitly contrast with alternative tools like 'latest_news' or provide when-not-to-use guidance.

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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TDQS

A4.1/5.0
Disambiguation5/5

Each tool has a detailed description clarifying its precise purpose, and even closely related tools (e.g., ask_pipeworx vs ask_pipeworx_grounded) are clearly differentiated by behavior and use case. No two tools appear to serve the same function.

Naming Consistency3/5

All names use snake_case, but the structural pattern is inconsistent: many follow verb_noun (compare_entities, resolve_entity), while others are noun-based (entity_profile, polymarket_arbitrage) or single verbs (subscribe, remember). This mix reduces predictability.

Tool Count3/5

With 32 tools, the server is quite large for an MCP server. While many tools are justified by the broad domain coverage, the high number can overwhelm agents and increase cognitive load, making it feel somewhat bloated.

Completeness4/5

The tool set covers a wide range of domains (company data, prediction markets, news, memory, subscriptions, etc.), and the generic ask_pipeworx and deep_research tools gateways to thousands of data sources, effectively filling gaps. However, some areas lack dedicated tools (e.g., weather, real estate) beyond the generic query.

Resources