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opentable-mcp

by chrischall
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TypeScript
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opentable_cancel

DestructiveIdempotent

Cancel an OpenTable reservation by providing the restaurant ID, confirmation number, and security token. Confirms the booking details before finalizing.

Instructions

Cancel an OpenTable reservation. Requires restaurant_id, confirmation_number, and security_token — all three come from opentable_list_reservations or opentable_book. Asks the user to confirm first: a confirmation prompt where the client supports one; otherwise the first call returns a preview and a confirmToken, and only a repeat call with that token proceeds; the prompt names the restaurant, date, time and party size from your dining dashboard (see MCP_CONFIRM_MODE). Refused when the confirmation_number belongs to a different restaurant.

Input Schema

NameRequiredDescriptionDefault
confirmTokenNoONLY for the two-step confirmation fallback (a client without MCP elicitation). The confirmToken from this same tool's phase-1 "confirmation-required" response, passed back ONLY after the user has seen that preview and explicitly approved it in chat — never on the first call, never invented, never reused. Call again with the same arguments. Ignored when the client supports elicitation.
restaurant_idYes
security_tokenYes
database_regionNoOpenTable's sharded-database region for the restaurant. Defaults to 'NA' (North America). Pass the venue's region (e.g. for UK/EU/APAC restaurants) when booking or cancelling outside North America — slot-lock, availability, and cancel route to the wrong database shard, or fail opaquely, when this is wrong. LIMITATION: not auto-derived from restaurant data (OpenTable's availability/booking responses don't surface the shard id), so non-NA bookings must set it explicitly.
confirmation_numberYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.2.1
    • removedInput schema / properties / confirm
      Removed value: -{
-  "description": "Must be true to proceed. Without this, the tool returns a preview.",
-  "type": "boolean"
-}
    • addedInput schema / properties / confirmToken
      Added value: +{
+  "description": "ONLY for the two-step confirmation fallback (a client without MCP elicitation). The confirmToken from this same tool's phase-1 \"confirmation-required\" response, passed back ONLY after the user has seen that preview and explicitly approved it in chat — never on the first call, never invented, never reused. Call again with the same arguments. Ignored when the client supports elicitation.",
+  "type": "string"
+}
  2. Changed1 schema field changedv1.0.0
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  3. First observedv0.14.3

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already flag destructiveHint=true and idempotentHint=true, but the description goes well beyond them: it documents the two-phase confirmation flow (preview + confirmToken, only a repeat call proceeds), the elicitation-capable client path, the MCP_CONFIRM_MODE dependency, and the cross-restaurant refusal rule. That is the operational reality an agent must plan around for a destructive call.

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

Conciseness4/5

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

Purpose is front-loaded and nearly every clause carries information, but the second half is a single long run-on sentence packing confirmation flow, refusal rule, and prompt contents together. It remains readable, though a break or two would improve scannability.

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?

There is no output schema, so the description takes responsibility for describing the return behavior — the phase-1 'confirmation-required' preview and confirmToken — which it does. Combined with the schema's confirmToken and database_region notes, an agent has everything needed to call this destructive tool correctly.

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 only 40%, so the description must compensate — and it does for restaurant_id, confirmation_number, and security_token by stating they all originate from opentable_list_reservations or opentable_book. The remaining detail (confirmToken lifecycle, database_region shard caveat) is carried in the schema descriptions themselves, so the split leaves no parameter truly unexplained.

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?

Opens with a specific verb+resource ('Cancel an OpenTable reservation') that an agent can distinguish immediately from sibling mutators like opentable_modify or opentable_book. It also states the three required inputs and their provenance, so the agent knows exactly what this tool needs.

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

Usage Guidelines5/5

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

Explicitly routes parameter sourcing to opentable_list_reservations or opentable_book, and spells out the confirmation precondition and the one case where the call is refused (confirmation_number belonging to a different restaurant). The when-to-use and when-not-to-use conditions are both covered.

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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