Skip to main content
Glama

Servd Agentic Ordering

Get venue details

get_venue
Read-onlyIdempotent

Get one venue’s opening hours, current open state, pickup and delivery availability, published policies, and available agent-order payment mode.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesThe venue slug.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
urlYes
nameYes
slugYes
emailYes
hoursYes
phoneYes
ratingYes
addressYes
logoUrlYes
openNowYes
coverUrlYes
currencyYesISO 4217 currency code.
orderUrlYes
policiesYes
timezoneYes
serviceModesYes
agentOrderingYes
acceptsReservationsYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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 context about the returned content (current open state, availability, policies, payment mode) but does not disclose behaviors such as not-found handling or data freshness. This is acceptable given the strong annotation coverage.

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 sentence that front-loads the action and subject, then lists data fields with no filler words. Every element earns its place, and it is easy to parse quickly.

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?

The tool has one required param, a documented schema, an output schema, and safe-read annotations. The description clearly states what data will be returned, so an agent has everything needed to invoke it correctly. No missing prerequisites or edge-case instructions are necessary for this simple read operation.

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?

The only parameter, slug, is fully documented in the schema ('The venue slug.') with 100% schema description coverage. The description confirms the singular nature of the lookup but adds no new semantic detail beyond the schema, so the 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?

The description states a specific verb ('Get') and resource ('one venue') and enumerates the exact data returned: opening hours, current open state, pickup/delivery availability, policies, and payment mode. This clearly distinguishes it from siblings like find_venues (search) and get_menu (menu items), so an agent can confidently select this tool for venue-level details.

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 description gives clear context: it is for retrieving details for exactly one venue, identified by slug. It does not explicitly state when not to use it or mention alternatives like find_venues, but the singular scope and field list make the primary use case unambiguous.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.3/5.0
Disambiguation5/5

Each tool targets a distinct step in the ordering workflow: venue discovery, venue details, menu retrieval, cart validation, order placement, and order status checking. Even find_venues and get_venue are clearly separated by list/search versus single-venue detail.

Naming Consistency5/5

All tool names follow a consistent lowercase verb_noun pattern: find_venues, get_venue, get_menu, validate_cart, place_order, check_order. The verbs are distinct yet predictable, and there is no mixing of casing or naming styles.

Tool Count5/5

Six tools is well-scoped for an agentic ordering server. Each tool supports a necessary phase of the ordering flow without redundancy or unnecessary bulk.

Completeness4/5

The core ordering lifecycle is covered: discover venues, inspect venue details, fetch menus, validate carts, place orders, and poll order status. The main gap is the lack of a cancel_order or update_order tool, so order management after placement is limited.

Resources