Jardins

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

A4.6/5.0

Behavior5/5

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

No annotations are provided, so the description fully bears the burden. It discloses the typo-tolerant/accent-insensitive matching, ranking by relevance, the server-side open_now computation, the ALL-must-match constraint for attributes, and the exact structure of results (open_now boolean, attributes array, delivery array with platform/url, rating, hours in Google Maps periods).

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 each sentence adds value. It is well-structured: purpose first, then q behavior, filter usage, result details. Slight reduction in wordiness could improve conciseness, but it remains focused and informative.

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 the tool has 6 parameters, no output schema, and no annotations, the description covers all key behaviors and result details. It misses explicit mention of the limit parameter (described in schema only) and could clarify the neighborhood context, but overall it is quite complete.

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

Parameters5/5

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

Schema coverage is 100%, but the description adds significant meaning beyond parameter names: it explains the q matching behavior (accent-insensitive, typo-tolerant), the open_now filter semantics (computed server-side), the attributes filter logic (ALL must match), and the result structure details (delivery array format, hours format, amenity slugs).

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 it searches for places (restaurants, cafes, shops, etc.) in a neighborhood. It uses a specific verb ('Search') and resource ('places'), and distinguishes from sibling tools like get_place (singular) or search_dishes (specific to dishes).

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 explains the search behavior and filter usage (category, neighborhood, open_now, attributes). It implies when to use this tool (generic place search) vs siblings (e.g., get_place for specific place, search_dishes for dishes), but does not explicitly state exclusions or alternatives.

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

All Jardins 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 action and resource, such as booking, checking availability, listing events, or searching dishes. No two tools appear to overlap in purpose, and descriptions clearly differentiate them.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern (e.g., create_booking, get_availability, list_events, search_places). The prefixes (create, get, list, search, request, reserve, rsvp, submit) are uniformly applied, and there is no mixing of cases or styles.

Tool Count4/5

With 28 tools, the server covers a broad feature set for a neighborhood directory, including bookings, store, events, loyalty, menus, movies, and more. While slightly high, each tool serves a distinct purpose and is justifiable.

Completeness5/5

The tool surface appears complete for the domain: search, details, booking flows, store purchases, events, loyalty, reviews, blog, offers, profiles, forms, and FAQ are all covered. There are no obvious dead ends, and operations for CRUD or lifecycle are present where needed.

Resources

Need Help?