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mcp-server

by io.alterlab
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Get News Headlines

alterlab_news
Read-onlyIdempotent

Search aggregated news headlines from curated public sources: headline, URL, source, published time, author, image, short snippet and category. Use to find what is being reported on a topic. Served from a cache that refreshes about every 15 minutes, so a call never triggers a fetch; free and keyless, no credits are spent. Returns metadata only, not article text: to read an article, call alterlab_scrape on its URL. Cite results as 'News via AlterLab'.

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": "alterlab_news"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMax items (default 20)
queryNoText to match in headline or snippet
sinceNoISO 8601 time; only items published after it
sourceNoSource id, e.g. bbc, npr, guardian-world, aljazeera
categoryNoCategory, e.g. world, technology, business, science, sports, general
languageNoLanguage code, e.g. en, de

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

Goes well beyond the annotations by disclosing cache behavior (~15 minute refresh, a call never triggers an upstream fetch), cost model (free, keyless, no credits spent), and scope limits (metadata only, no article body). It even specifies the required attribution string, which is behavioral context an agent cannot infer from readOnlyHint/idempotentHint alone.

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?

Four tight sentences, each doing distinct work: what it returns, when to use it, caching/cost behavior, and the escalation path plus citation. Nothing is repeated from the schema and nothing is filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description compensates by listing the returned fields, and for a keyless read-only search tool it also covers freshness, cost, and the follow-up call needed for full text. An agent has everything required to invoke it correctly and to act on the results.

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% and every parameter (limit, query, since, source, category, language) is documented in the schema itself with examples, so the baseline of 3 applies. The description adds no per-parameter meaning such as match semantics for query or how since interacts with cache freshness.

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?

Starts with a specific verb and resource ('Search aggregated news headlines from curated public sources') and enumerates exactly what each result contains (headline, URL, source, published time, author, image, snippet, category). This makes it distinguishable from general web-search siblings like alterlab_search and alterlab_serp without opening any schema.

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?

Gives a clear use case ('Use to find what is being reported on a topic') and an explicit handoff rule: for full article text, call alterlab_scrape on the URL. It does not state when a caller should prefer this over alterlab_search or alterlab_serp for news-like queries, so the routing against those two siblings is left implicit.

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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