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easytable-mcp

by chrischall
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TypeScript
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easytable_create_booking

Destructive

Creates a restaurant reservation from date, time, party size, and guest details using your open booking-widget tab, after confirming the preview.

Instructions

Create a restaurant booking. Reads the Cloudflare Turnstile token from your signed-in booking-widget tab (via the bridge) and submits it with the reservation — so a book.easytable.com/book/?id= tab must be open and loaded. 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 (see MCP_CONFIRM_MODE). The first call makes NO network call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesRestaurant id — the `id` in a book.easytable.com/book/?id=<id> link.
dateYesBooking date, ISO YYYY-MM-DD (from easytable_list_dates).
langNoWidget language code (en, se, da, …). Defaults to en.en
nameYesGuest name on the booking.
timeYesTime slot HH:MM (from easytable_list_times).
typeYesBooking area/type id from easytable_list_types.
emailNoGuest email.
eventNoOptional event id.
mobileYesGuest mobile in E.164 (e.g. +46701234567).
commentNoFree-text note / special requests.
companyNoOptional company name.
personsYesParty size.
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.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.2.0
    • 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 / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  3. Changed1 schema field changedv0.4.1
    • changedInput schema / properties / email / pattern
      Previous value: -"^(?!\\.)(?!.*\\.\\.)([A-Za-z0-9_'+\\-\\.]*)[A-Za-z0-9_+-]@([A-Za-z0-9][A-Za-z0-9\\-]*\\.)+[A-Za-z]{2,}$"New value: +"^(?:[A-Za-z0-9_'+\\-]+\\.)*[A-Za-z0-9_'+\\-]*[A-Za-z0-9_+-]@(?:[A-Za-z0-9][A-Za-z0-9\\-]*\\.)+[A-Za-z]{2,}$"
  4. First observedv0.0.0

TDQS

A4.3/5.0
Behavior5/5

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

Adds substantial behavior beyond the annotations: reads a Cloudflare Turnstile token via a bridge, requires a signed-in widget tab, prompts for confirmation, and critically discloses that the first call makes no network call and returns a preview + confirmToken. This is exactly the non-obvious operational detail the annotations do not carry.

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?

Front-loads the core purpose, then layers prerequisites and the confirmation protocol. It is dense and every sentence is load-bearing, though the confirm-flow explanation is lengthy relative to a single-tool description.

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 13-parameter mutation with no output schema, the description covers prerequisites, confirmation, and the no-network first call. It does not describe failure modes (e.g., unavailable slot, missing/mismatched token beyond the outline) or the eventual success response, leaving a small gap.

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 parameters are already well documented (id, date, time, type, confirmToken, etc.). The description adds linkage context (id as the widget link id, confirmToken as the phase-1 token) but 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.

Purpose5/5

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

States a specific verb+resource ('Create a restaurant booking') and clearly distinguishes itself from siblings like easytable_modify_booking and easytable_cancel_booking. An agent immediately knows this is the booking-creation tool.

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?

Gives concrete prerequisites (a loaded book.easytable.com/book/?id=<id> tab must be open) and explains the confirmation flow, including the MCP_CONFIRM_MODE fallback. It does not explicitly state when to prefer this over siblings (e.g., availability-check tools), but the operational context is strong.

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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