Skip to main content
Glama

Shortlist Pass Local Businesses

Get upcoming events and stops

get_upcoming_events

Upcoming published events and stops for one business — for a food truck, this is where it will be. Each has a name, ISO start/end with the local offset, location name and address, whether pre-orders are open for that stop, and when they are, the pickup time slots still available with remaining capacity (null means no cap). Recurring events carry a recurrence description and the next date. Cancelled and test events are never included. To order for a stop, send the customer to its order_url.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
subdomainYesThe business subdomain, e.g. "nitos"

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses data-shape guarantees (ISO timestamps with local offset), capacity semantics (null = no cap), exclusions (cancelled and test events never included), and recurrence behavior. It omits auth requirements, pagination, and result limits, keeping it short of a 5.

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-loaded with the resource and scope, and each subsequent sentence adds distinct value (returned fields, capacity semantics, exclusions, ordering pointer). The return-field enumeration is long but justified since there is no output schema.

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?

No output schema exists, and the description compensates thoroughly by enumerating returned fields and their edge-case semantics. Combined with a trivial one-parameter input schema, an agent has everything needed to call and interpret the result.

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?

Only one parameter (subdomain) with 100% schema description coverage, so the schema already fully documents it. The description adds nothing about the parameter, which is the correct baseline when structured data does the work.

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?

States a specific resource (upcoming published events and stops for a business) with clear scope, and even clarifies the food-truck framing. It does not explicitly differentiate from siblings, but get_business/get_menu/search_businesses cover wholly different domains, so confusion is unlikely rather than impossible.

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?

Usage is implied rather than stated — the description tells the agent to route customers to order_url for a stop, but never says when to call this tool versus alternatives, or any prerequisites. No when/when-not guidance and no named alternatives.

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.

Resources