TableSpark Restaurants

Check table availability

check_table_availability

Read-onlyIdempotent

Live table times for a date and party size, from the restaurant's own booking system. Each time comes with a link to book it on the restaurant's website. Does not make a booking.

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": {
      "restaurant_id": "<restaurant_id>",
      "date": "<date>",
      "party_size": "<party_size>"
    },
    "name": "check_table_availability"
  }
}

Input Schema

Name	Required	Description
`date`	Yes	Date in YYYY-MM-DD (UK local date).
`party_size`	Yes	Number of guests, including the person booking.
`restaurant_id`	Yes	The restaurant_id returned by search_restaurants (for example "oak-nosh").
`preferred_time`	No	Optional time to find the closest slot to (HH:MM).

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 10, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already cover the safety profile (read-only, idempotent, non-destructive, closed-world), so the description adds real value on top: it discloses the data source (the restaurant's own booking system), that times are live, and that every result carries an outbound booking link. Still missing are behavior for empty results and any staleness/rate considerations.

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 short sentences, front-loaded with what the tool returns and its source, then the result shape, then the boundary condition. No filler or repetition.

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 usefully characterizes the return (individual time slots each with a booking link), which is the key thing an agent needs. It leaves the empty-availability case and any additional slot fields unstated, a minor gap for a simple read 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%, so the schema already documents format, ranges, and the restaurant_id provenance. The description only echoes 'date' and 'party size' and says nothing about preferred_time being a nearest-slot hint, so it adds no meaning beyond the structured fields.

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 resource and scope: live table times for a given date and party size, sourced from the restaurant's own booking system. It implicitly separates itself from the booking-action siblings by noting each time carries a booking link, though it never names an alternative tool explicitly.

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 context for use is clear (checking availability for a date and party size) and there is one explicit when-not: 'Does not make a booking,' which routes the agent away from treating this as a reservation tool. It stops short of naming get_booking_link or search_restaurants as the prerequisite/next step, so the routing is only partly spelled out.

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

All TableSpark Restaurants tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?