typesearch

Search news

search_news

Read-only

Search recent news on any topic across a curated index of news outlets worldwide, judged by a relevance model. Returns the matching articles: title, link, source, date, country and language, standfirst, and short excerpts in the modes that read. Use it for current events and for what outlets reported about a company, person, place or topic. Defaults: mode "fast" (US$1.40 per 1,000 searches) and the last 7 days; mode "ultra" judges headlines only, for US$1.00.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`days`	No	Only the last N days, 1 to 365. Defaults to 7 unless published_after or published_before are given.
`mode`	No	fast (default): headlines and standfirsts · ultra (cheapest): headlines only · normal: also reads the best matches · deep: reads more, finds the topic in other words too.	fast
`index`	No	Optional: search your own custom index (its id, idx_…) instead of the news index: your own list of URLs, sitemap or feed, created at https://app.typesearch.ai/indexes or with POST /v1/indexes. Same modes and prices; no date filter unless you pass days or dates.
`query`	Yes	What to look for, in any language: a topic, event, person, company or place, such as "inflation in Argentina" or "OpenAI funding".
`countries`	No	Only sources from these countries: ISO 3166-1 alpha-2 codes, such as ["AR"] or ["US", "GB"].
`languages`	No	Only sources that publish in these languages: ISO 639-1 codes, such as ["es"] or ["en", "pt"].
`max_results`	No	How many results, 1 to 25. Defaults to 10.
`exclude_domains`	No	Never these domains or paths.
`include_domains`	No	Only these domains or paths, such as example.com or example.com/sports.
`published_after`	No	Published on or after this date: 2026-09-25, or a date-time with offset.
`published_before`	No	Published on or before this date; a bare date includes that whole day.

Output Schema

TableJSON Schema

Name	Required	Description
`mode`	Yes
`query`	Yes
`cached`	No
`results`	Yes
`cost_usd`	Yes
`warnings`	No
`incomplete`	No	The time or token budget ran out: there may be more.
`request_id`	Yes
`near_misses`	No	Only when nothing matched: the closest articles, which may not be about it.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 26, 2026

addedInput schema / properties / index

Added value: +{
+  "description": "Optional: search your own custom index (its id, idx_…) instead of the news index: your own list of URLs, sitemap or feed, created at https://app.typesearch.ai/indexes or with POST /v1/indexes. Same modes and prices; no date filter unless you pass days or dates.",
+  "pattern": "^idx_[a-z0-9]{6,40}$",
+  "type": "string"
+}

First observedSep 25, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With readOnlyHint=true and openWorldHint=true already in annotations, the description still adds meaningful behavior context: exact pricing per mode (US$1.40 vs US$1.00 per 1,000 searches), the default 7-day window, and the fact that some modes 'read' article bodies while others judge headlines only. No contradiction with the read-only/open-world hints.

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?

Three sentences with zero filler: purpose first, then return fields and use cases, then defaults and pricing. Every sentence earns its place, and the most critical scoping info ('any topic', 'curated index', 'recent') is front-loaded.

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 an 11-parameter tool this is well covered: the schema documents all parameters at 100%, an output schema exists (so return values need no elaboration), and the description supplies use cases, defaults, and pricing. Minor gaps — no guidance on ordering, no explicit distinction from siblings, no note on the custom-index caveat — but nothing an agent needs to invoke it correctly is missing.

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%, so the schema carries most parameter semantics, but the description adds decision-relevant information beyond it: the cost-per-1,000-searches for choosing between modes and the default time window. This genuinely helps an agent select mode/value correctly rather than merely restating enum options.

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+resource ('Search recent news on any topic across a curated index of news outlets worldwide') and adds the relevance-model criterion. The stated use cases ('current events', 'what outlets reported about a company, person, place or topic') and the return-field list make the tool's distinct job unambiguous versus siblings find_similar and get_contents, even though neither is named.

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 clearly states when to use it ('Use it for current events and for what outlets reported about a company, person, place or topic') and gives default behavior (7-day window, fast mode). However, it never names alternatives or states when NOT to use it, such as redirecting to find_similar for similarity matching or get_contents for full article retrieval — so exclusions are left to inference.

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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