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opentable-mcp

by chrischall
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TypeScript
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opentable_search_restaurants

Read-only

Find restaurants on OpenTable by cuisine, location, or name, returning details like rating, price band, and URL. Use opentable_find_slots to check booking availability.

Instructions

Search OpenTable for restaurants. Returns matching restaurants with cuisine, neighborhood, price band, rating, description, and URL. Does NOT include bookable slot tokens — use opentable_find_slots for a specific venue to check availability.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoYYYY-MM-DD. Affects search ranking but not returned slots.
termNoFree-text query (cuisine or restaurant name)
timeNoHH:MM (24h). Default 19:00 when date is set.
viewNoResponse shape: "compact" (default) drops fields the response already carries elsewhere; "full" returns every field this server understands. compact strips image/avatar URLs from the response; "full" returns OpenTable's payload untouched. No field projection: this server has no verified record of which OpenTable fields matter, and inventing one would risk dropping a field a caller needs.
latitudeNo
locationNoCity / neighborhood / address — appended to the term. Prefer lat/lng when precise.
metro_idNoOpenTable metro id (e.g. 8 = SF Bay Area, 31 = Charlotte).
longitudeNo
party_sizeNoNumber of guests. Default 2.

Schema Changelog

Changes observed during successful MCP inspections.

  1. 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"
  2. Changed1 schema field changedv0.19.2
    • addedInput schema / properties / view
      Added value: +{
+  "description": "Response shape: \"compact\" (default) drops fields the response already carries elsewhere; \"full\" returns every field this server understands. compact strips image/avatar URLs from the response; \"full\" returns OpenTable's payload untouched. No field projection: this server has no verified record of which OpenTable fields matter, and inventing one would risk dropping a field a caller needs.",
+  "enum": [
+    "compact",
+    "full"
+  ],
+  "type": "string"
+}
  3. First observedv0.14.3

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the read-only nature is covered. The description adds valuable behavioral context by stating exactly what fields are returned and, crucially, that slot tokens are not included—information an agent needs to avoid assuming availability is present. This goes beyond the annotation without contradicting it.

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 two sentences with zero filler. The first sentence delivers the core purpose and output, and the second sentence provides a critical exclusion plus a pointer to the sibling. It is front-loaded, efficient, and every word earns its place.

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?

For a search tool with no required parameters and no output schema, the description covers the essential behavioral contract: what it returns, what it omits, and when to use a different tool. It does not explain parameter interactions (like date affecting ranking), but those are already in the schema. Minor gaps like pagination or result limits are not critical for correct invocation.

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 78%, so most parameters already have their own explanations in the schema. The tool description adds no new parameter-level meaning; it only restates the return fields. Per the rubric, high schema coverage sets a baseline of 3, and the description does not exceed that baseline.

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 description opens with a clear verb and resource: 'Search OpenTable for restaurants' and lists specific returned fields (cuisine, neighborhood, price band, rating, description, URL). It explicitly differentiates itself from opentable_find_slots by stating it does NOT include bookable slot tokens, making its scope unambiguous among siblings.

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?

It gives an explicit when-not and names the alternative: 'Does NOT include bookable slot tokens — use opentable_find_slots for a specific venue to check availability.' This directly routes the agent away from the most likely confusion and toward the correct sibling, which is exactly what good usage guidance looks like.

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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