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Search hotels by description

get_data_hotels_semantic_search
Read-onlyIdempotent

Search hotels using natural language queries. AI interprets intent to return semantically matching hotels with relevance scores and attributes, not just keyword matches.

Instructions

Overview

Beta Feature - Search hotels using natural language queries. Uses AI to understand search intent and find hotels that match the meaning, not just keywords.

When to Use

  • Natural language search - Let users search with phrases like "romantic getaway in London"

  • Intent-based matching - Find hotels matching the vibe or style, not just location

  • Conversational search - Support natural language hotel discovery

  • Semantic matching - Get hotels that semantically match the query

What You Get

  • Matching hotels - Hotels that semantically match your query

  • Semantic attributes - Tags, persona, style, location_type, and story for each hotel

  • Relevance scores - How well each hotel matches the query

  • Hotel metadata - ID, name, photos, address, city, country

Example Queries

  • "Romantic getaway in London with Italian vibes"

  • "Hotels near Paris"

  • "Family-friendly beachfront hotels"

Quick Start

Provide a natural language query parameter. Returns hotels with semantic matching scores and attributes.

Note: This is a beta feature and may be subject to changes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results to return. Default is 3.
queryYesSemantic search query. This can be a natural language description of what you're looking for, e.g. 'romantic getaway in london with italian vibes'
min_ratingNoMinimum hotel rating to filter results. Default is 0 (no minimum rating filter).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already establish the safe read-only, idempotent, open-world profile. The description adds real value beyond them: beta status/subject to change, the semantic fields returned (tags, persona, style, location_type, story), relevance scores, and the hotel metadata payload — meaningful context for a tool with no output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with an overview and useful sections, but heavy markdown scaffolding carries redundancy: four 'When to Use' bullets that say essentially the same thing, and 'Matching hotels - Hotels that semantically match your query' is a tautology. It could be roughly half the length.

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?

With no output schema, the description correctly fills the gap via 'What You Get' enumerating return fields and scores, and flags beta instability. The main remaining gap is the absence of differentiation from the other hotel-search siblings, which matters given the crowded sibling set.

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 the schema already documents query, limit (default 3), and min_rating (default 0). The description reinforces the query parameter and supplies concrete example queries, but adds no syntax or format detail beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource (semantic/natural-language hotel search) and describes the mechanism (AI intent matching) clearly. However, it never differentiates itself from the several closely-named hotel-search siblings (get_data_hotel_search, get_data_hotel_ask, get_data_hotels), so an agent cannot tell which search to pick from the description alone.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is a 'When to Use' section, but all four bullets restate the same idea (natural-language / intent / conversational / semantic search) rather than giving distinct conditions. No when-not-to-use guidance and no alternative tools are named, so routing among the hotel search siblings is left to inference.

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