Skip to main content
Glama

Encontrar profissionais

find_providers
Read-onlyIdempotent

Encontra profissionais reais perto de um lugar para uma necessidade. Ex.: need="instalar 3 ventiladores", where="Tijuca, Rio de Janeiro", min_rating=4.5, max_price_brl=350. Retorna perfis estruturados (nota, avaliações, distância, preço quando informado) e uma tela com cards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoLatitude (busca geolocalizada: use com lng quando o usuário compartilhar a localização)
lngNo
needYesO que o usuário precisa, com as palavras dele
sortNo
limitNo
nicheNoSlug exato do tipo de profissional (de list_categories), ex.: "motorista", "pedreiro". Quando informado, vence a interpretação do texto.
whereNoBairro e/ou cidade, ex.: "Tijuca, Rio de Janeiro" ou "Pinheiros SP"
serviceNoSubcategoria exata, a service_key de search_services (ex.: "piscina/limpeza"). Prioriza quem faz exatamente isso, sem esconder o resto do tipo.
radius_kmNoRaio da busca em km a partir de lat/lng ou do lugar (padrão: 5 a 15 km conforme o lugar)
min_ratingNo
min_reviewsNo
emergency_24hNoSó quem atende 24 horas / emergência
max_price_brlNoMantém quem não informou preço (cobra por orçamento)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalYes
providersYes
loqal_pageYes
understoodYes
related_nichesNoPresente quando o tipo pedido ainda não tem ninguém na região e a lista é de tipos afins

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/openWorld/non-destructive, so safety is covered. The description adds genuinely new context: it returns structured profiles (rating, reviews, distance, price) plus a UI 'tela com cards', and it discloses that max_price_brl keeps providers who quoted by orçamento rather than price. Missing only pagination/limit behavior.

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?

Three front-loaded sentences: purpose, worked example, return shape. Every part earns its place, though the example is somewhat long and consumes space that could have covered uncovered parameters.

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?

For a 13-parameter search with an output schema and rich annotations, the description covers intent, a realistic example, key parameter precedence rules, and return contents. Gaps are minor (sorting/limit semantics), and the output schema removes the need to explain return values in depth.

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 coverage is 62%, and the description supplies a full example that demonstrates how need/where/min_rating/max_price_brl combine, plus a clarifying hint for max_price_brl. It does not compensate for the undocumented params (sort, limit, min_reviews), so it sits at the baseline for partial coverage.

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 verb and resource ('Encontra profissionais reais perto de um lugar para uma necessidade') and grounds it with a concrete example call. It implicitly separates itself from get_provider/compare_providers by being a discovery search, but never names those siblings explicitly, so differentiation is left partly to inference.

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 worked example shows how to invoke it, and it notes that niche 'vence a interpretação do texto' and that service prioritizes exact matches — useful behavioral guidance. However there is no explicit when-to-use-this-vs-alternatives statement relative to siblings like search_services or compare_providers, so usage is only implied.

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