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CraveUp MCP Server

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by craveup

Set location street address

set_location_address
Idempotent

Update a location's address for storefront and delivery/pickup. Preview changes via dry-run then apply with the returned digest; geocoding is automatic.

Instructions

Update a location address (shown on the storefront and used for delivery/pickup). Omit lat/lng — the server geocodes the address. Requires craveup login.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNo
lngNo
cityYes
modeNoPreview by default. Apply requires the exact returned planDigest.dry-run
stateYesState, region, or emirate
streetYes
countryYes
zipCodeYes
timezoneYesExplicit IANA timezone for this physical location, for example America/Los_Angeles
locationIdNoOmit to use CRAVEUP_LOCATION_ID
planDigestNoExact digest returned by a dry-run of the same arguments.
streetOptionalNoSuite / unit
confirmationTokenNoRequired exact phrase for destructive, paid, or release operations.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
modeYes
statusYes
changesYes
summaryYes
operationYes
planDigestYes
environmentYes
nextActionsYes
schemaVersionYes
Install Server

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already cover read-only/destructive intent, and the description adds meaningful behavioral context: the address is geocoded server-side when lat/lng are omitted, and a craveup login is required. This goes beyond the structured annotations without contradicting them.

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 three short sentences, front-loaded with the core purpose, and every sentence adds value. It avoids repetition of schema details and annotations.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 13 parameters, a default dry-run mode, and an apply mode that requires planDigest and possibly confirmationToken. The description omits this two-phase workflow entirely, which is a critical gap for an agent trying to invoke the tool safely and correctly.

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 54%, so the description carries partial responsibility for parameter meaning. It usefully explains that lat/lng should be omitted and geocoding will occur, but it leaves the dry-run/apply mode, planDigest, and confirmationToken semantics to the schema.

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?

The description clearly states the tool updates a location address and provides context about where that address is used (storefront, delivery/pickup). It does not explicitly distinguish this tool from siblings such as create_location or get_location_settings, so it misses the top tier.

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

Usage Guidelines3/5

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

The description gives useful context—addresses appear on the storefront and are used for delivery/pickup—and an instruction to omit lat/lng so the server geocodes. However, it does not mention when to prefer this tool over alternatives or provide any exclusions.

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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