Moema

search_places

Search for places (restaurants, cafes, shops, etc.) in this neighborhood. The q match is accent-insensitive and typo-tolerant ("acai" finds "Açaí", "restaurnt" finds "Restaurante"), ranked by relevance. Compose filters for multi-condition queries: category, neighborhood, open_now (true = open at this exact moment), and attributes (amenity slugs, ALL must match). Each result includes a precomputed open_now boolean, an attributes array (amenity slugs), a delivery array of curated delivery-app deep-links (ifood, rappi, 99food, uber-eats — each { platform, url }), rating, and structured hours (Google Maps periods: day 0=Sun–6=Sat, time "HHMM"). Common amenity slugs: wifi, outdoor-seating, wheelchair, dog-friendly, delivery, takeaway, reservations, live-music, vegan, gluten-free (availability varies per place).

Input Schema

TableJSON Schema

Name	Required	Description
`q`	No	Free-text term matched against place name and address — accent-insensitive and typo-tolerant.
`limit`	No	Max results to return (default 20, max 100).
`category`	No	Filter by category label (e.g. "Café"). Case-insensitive substring match.
`open_now`	No	When true, return only places open at the current local time (computed server-side from their opening hours).
`attributes`	No	Amenity slugs a place must ALL have, e.g. ["wifi","outdoor-seating"]. Common slugs: wifi, outdoor-seating, wheelchair, dog-friendly, delivery, takeaway, reservations, live-music, vegan, gluten-free.
`neighborhood`	No	Filter by neighborhood name. Case-insensitive substring match.

TDQS

A4.3/5.0

Behavior5/5

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

No annotations are provided, so the description fully carries the transparency burden. It details search behavior (accent-insensitive, typo-tolerant), result fields (open_now, attributes, delivery, rating, hours), and common amenity slugs, providing comprehensive behavioral insight.

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?

The description is fairly long but well-structured with front-loaded purpose and subsequent detail. Every sentence adds valuable information; however, it could be slightly more concise without losing clarity.

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?

Given 6 parameters, no output schema, and no annotations, the description adequately covers all parameters and explains result fields. Some minor details like pagination for limit are present. No critical gaps identified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, baseline 3. The description adds meaningful context beyond schema: explains typo-tolerance for q, case-insensitive substring for category, server-side open_now computation, mandatory ALL for attributes, and neighborhood substring match. This enriches parameter understanding.

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 clearly states the action ('Search for places') and the resource ('restaurants, cafes, shops, etc.'). It distinguishes from sibling tools like search_dishes by focusing on general place search.

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 explains how to use filters but does not explicitly state when to use this tool versus alternatives like get_place or search_dishes. Usage context is implied but not directly guided.

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

All Moema tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.2/5.0

Disambiguation5/5

Each tool targets a distinct resource and action (e.g., create_booking, create_checkout, request_reservation, reserve_event_tickets, rsvp_event all differ in purpose). Even similar-sounding tools like search_places and list_categories serve complementary roles (search vs taxonomy). No ambiguity.

Naming Consistency5/5

All 28 tool names follow a consistent verb_noun pattern in snake_case (e.g., create_booking, get_availability, list_blog_posts). No mixing of conventions or vague verbs.

Tool Count4/5

28 tools is above the typical 3-15 range but appropriate for the comprehensive scope of a neighborhood directory covering multiple Wix integrations (bookings, events, store, restaurants, etc.). Slightly heavy but well-scoped.

Completeness5/5

The tool surface covers the full lifecycle of a neighborhood directory: search, details, reviews, menus, booking, events, movies, offers, forms, FAQs, loyalty, etc. No obvious gaps; each domain has create/read/update/delete where applicable.

Resources

Need Help?