Dubai Table

Check availability

check_availability

Read-onlyIdempotent

Tables still free at a venue on a date, from the live floor plan minus tables already requested or confirmed. Filter by party size, zone or maximum minimum-spend. Each table carries its zone, seats and minimum spend in AED.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "venue": "<venue>",
      "date": "<date>"
    },
    "name": "check_availability"
  }
}

Input Schema

Name	Required	Description
`date`	Yes	YYYY-MM-DD
`zone`	No	Restrict to one zone, e.g. Stage, Terrace, Veranda.
`party`	No	Number of guests; returns tables seating party..party+4.
`venue`	Yes	Venue id or name (billionaire, gigi, bagatelle, lepiaf, verde, raspoutine, coucou) — or an event name like "The List".
`max_min_spend`	No	Only tables with a minimum spend at or under this, AED.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 16, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations confirm read-only, idempotent and non-destructive, so safety is covered. The description adds valuable context about the data source (live floor plan minus requested/confirmed) and return fields (zone, seats, minimum spend in AED). It doesn't discuss rate limits or errors, but this exceeds the lower bar set by annotations.

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, front-loaded with the core purpose and no waste. Each sentence adds distinct value: scope, filtering, and returned fields.

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?

Given the output schema exists, the description needn't explain return values, yet it helpfully summarizes them. Missing explicit guidance on when to use this vs. alternatives like show_tables, but overall complete for a 5-param tool.

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 coverage is 100% and all parameters are fully described in the schema. The description adds no extra syntax or format details, so baseline 3 is appropriate.

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?

States a specific verb+resource ('Tables still free at a venue on a date') and clarifies the source ('live floor plan minus tables already requested or confirmed'), which distinguishes it from siblings like show_tables and request_table.

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?

Implies use for pre-booking availability search, but does not explicitly compare to alternatives like show_tables or request_table. Clear context is provided but no exclusions.

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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