Skip to main content
Glama
QasperAI

@qasperai/mcp-server

Official
by QasperAI

get_business_info

Read-only

Retrieve detailed business information including name, type, contact details, working hours, and profile image. Use natural-language attribute details to assess if a business fits user needs.

Instructions

Get business information including name, type, service area, contact details, working hours, supported languages, enabled features, and a profile image (logo or personal photo) when the owner has uploaded one. Use 'attributeDetails' (natural-language sentences about the business's offerings, approach, and specialties) to reason about fit for the user. The 'cardChips' and 'cardChipGroups' fields are UI-only display data — ignore them. The response echoes the exact slug; reuse it verbatim in later tool calls. Always available for any business.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesThe exact URL slug returned by search_businesses (e.g. 'nikos-plumbing-a3f2'). Copy it verbatim.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.6

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the readOnly and openWorld annotations, the description adds valuable behavioral details: it notes that profile images are only present if uploaded, identifies cardChips/cardChipGroups as UI-only and instructs to ignore them, and mentions that the slug is echoed for reuse. These disclosures go well beyond the structured annotations and greatly aid the agent's decision-making.

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 compact paragraph with each sentence conveying essential guidance: what fields are returned, how to use attributeDetails, which fields to ignore, and the slug echo behavior. No superfluous content; the structure is straightforward and front-loaded.

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?

Given the single parameter and no output schema, the description thoroughly explains the return contents and gives actionable guidance on using attributeDetails and ignoring UI fields. It is complete for the tool's purpose, with no additional clarification needed.

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 sole parameter 'slug' is fully documented in the schema with format and source instructions ('returned by search_businesses... copy it verbatim'). The description reinforces the reuse instruction but adds no new semantic meaning beyond the schema, so a baseline score of 3 is appropriate given the 100% schema coverage.

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 tool's function: retrieving business information, and enumerates the specific fields returned (name, type, service area, etc.). It distinguishes this from sibling tools by focusing on a general business profile rather than specific aspects like services or pricing.

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?

It provides context that this tool is always available and that the slug should be sourced from search_businesses and reused verbatim. It also instructs the agent to use attributeDetails for reasoning about fit. However, it does not explicitly contrast with sibling tools like get_services or get_pricing, so exclusions are absent.

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