Highland Intel APIs

Web search

web-search

Read-only

Neural or keyword web search with highlights, for agents. Up to 10 results, public URLs only. Returns { query, results: [{ title, url, publishedDate, score, highlights }] }: up to 10 results, each with up to 3 highlights of 500 characters. Price: 8 credits (1 credit = 1 CAD cent) per successful call; input that does not match the schema is rejected before billing.

Input Schema

Name	Required	Description	Default
`type`	No	Search mode: auto (default), neural (semantic) or fast.	auto
`query`	Yes	Search query, 1 to 500 characters.
`numResults`	No	Results to return, 1 to 10.
`excludeDomains`	No	Never return results from these domains (up to 20).
`includeDomains`	No	Only return results from these domains (up to 20).
`startPublishedDate`	No	Only pages published on or after this date (YYYY-MM-DD, UTC).

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 28, 2026

TDQS

A4.5/5.0

Behavior5/5

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

It adds high-value operational context beyond schema and annotations, specifically outlining the full JSON output structure (including highlights) and the financial constraints (8 credits, 1 CAD cent).

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 highly efficient, combining function, constraints (10 results, public URLs), output structure, and cost into a single, well-ordered paragraph.

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?

The description is comprehensive. It covers the functional nature, the constraints of the data returned (highlights, limits), the output format, and the associated cost, making it complete for agent decision-making.

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%. Therefore, the baseline score of 3 is appropriate, as the description is not required to compensate for a lack of parameter detail.

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 tool clearly states it performs 'Neural or keyword web search' and specifies it is 'for agents,' distinguishing it from generic web crawling or parsing 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 defines a clear boundary by stating it searches 'public URLs only.' While it doesn't explicitly compare its use case against a specific sibling tool, it provides necessary operational scope.

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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