kb-newspapers-mcp

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get_newspaper_timeline

Find when a historical event was most reported or which newspapers covered it by aggregating search results by year or newspaper title.

Instructions

Get the temporal or newspaper distribution statistics for a search term.
Useful to discover when an event was reported most frequently or which newspapers covered it.

Args:
    query: Search term (e.g. 'kolera', 'ångbåt', 'Sveriges riksdag').
    field: Aggregation target: 'datePublished' (distribution by year) or 'isPartOf' (distribution by newspaper title).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`field`	No		datePublished
`query`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 16, 2026

TDQS

A4.6/5.0

Behavior4/5

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

With no annotations, the description carries the behavioral burden. It explains that the tool aggregates by year or newspaper title and is a read-style 'Get' operation. It doesn't discuss rate limits or corpus scope, but for a simple statistics tool this is adequate.

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?

The description is compact: a one-sentence definition, a usage line, and a clear Args list. No filler or repeated schema information.

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?

For a two-parameter, read-only statistics tool with an output schema available, the description covers purpose, parameter semantics, and usage context. Nothing critical is missing for selecting and invoking it correctly.

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%, but the description fully compensates: it defines 'query' with concrete examples and defines 'field' with its two allowed values and their meanings ('distribution by year' vs 'distribution by newspaper title').

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 opens with a specific verb and resource: 'Get the temporal or newspaper distribution statistics for a search term.' It also names the two aggregation targets, which clearly separates it from sibling search/image/lookup tools.

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?

It gives clear context for when to use the tool ('discover when an event was reported most frequently or which newspapers covered it'), but it does not explicitly contrast with alternatives like search_newspapers or state when not to use it.

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

Deploy Server