CraveUp MCP Server

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TypeScript

Local

Read location store settings

get_location_settings

Read-onlyIdempotent

Retrieve store hours, scheduled-order flag, tax settings, and takeout configuration for a location to assess its operational setup.

Instructions

Fetch store hours, scheduled-order flag, tax settings, and takeout config for a location. Requires craveup login (Clerk session).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_location_settings"
  }
}

Input Schema

Name	Required	Description	Default
`locationId`	No	Omit to use CRAVEUP_LOCATION_ID

Output Schema

Name	Required	Description	Default
`data`	No
`mode`	Yes
`status`	Yes
`changes`	Yes
`summary`	Yes
`operation`	Yes
`planDigest`	Yes
`environment`	Yes
`nextActions`	Yes
`schemaVersion`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.6.1Aug 31, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context by specifying the authentication requirement and exactly which settings are fetched. No contradiction with 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?

The description is a single, tightly packed sentence that front-loads the action and the data being fetched, followed by the auth requirement. There is no filler, redundancy, or restating of the tool name.

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?

For a read-only tool with one optional parameter, the description is complete: it states what is returned, the authentication needed, and the scope. The output schema handles return-value documentation, and annotations handle the safety profile. No critical information is missing.

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%, and the single optional parameter locationId is fully documented in the schema, including the fallback to CRAVEUP_LOCATION_ID. The description adds no additional parameter-level semantics, so it meets the baseline 3 for high schema coverage.

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 uses a specific verb ('Fetch') and names the exact resource: store hours, scheduled-order flag, tax settings, and takeout config for a location. This clearly distinguishes it from sibling mutation tools like update_store_hours, set_scheduled_orders_enabled, and set_takeout_enabled, as well as from list_locations.

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 is clear: use this tool to retrieve read-only settings for a location. The description also states the authentication prerequisite (CraveUp login), which is important operational guidance. However, it does not explicitly name alternative tools for mutating those settings, so the when-not-to-use guidance is only implied.

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