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MCP Mercado Livre

get_questions

List buyer pre-sale questions on your Mercado Livre listings, newest first. Filter by UNANSWERED to find pending questions that need replies and protect conversion.

Instructions

List pre-sale questions buyers asked on the authenticated seller's listings, newest first. Use status='UNANSWERED' to find questions still waiting for a reply — that is the most common use case, since unanswered questions hurt conversion. Other status values: 'ANSWERED', 'DELETED', 'BANNED', 'DISABLED'. Use item_id to restrict to one listing. Each question comes back with its id (needed by answer_question), text, item id, status, creation date (ISO 8601), and the answer (text + date) when one exists. Requires authentication.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax questions to return, 1-50 (default 20)
statusNoFilter by question status: 'UNANSWERED', 'ANSWERED', 'DELETED', 'BANNED' or 'DISABLED'. Omit to list all; use UNANSWERED to find pending questions
item_idNoRestrict to a single item id, e.g. 'MLB123456789'

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden: it discloses the auth requirement, the default sort order (newest first), the enumerated status values, and the shape of each returned record. It does not discuss pagination or rate limits, but covers the core behavioral facts a caller needs.

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-loads purpose, then the primary-use-case tip, then status values, then the item_id filter, and finishes with the return shape and auth note. The return-field enumeration is somewhat long but earns its place given 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?

For a read-only list tool with no annotations and no output schema, the description supplies the missing pieces: auth requirement, ordering, return fields, and status semantics. Nothing an agent needs to invoke it correctly is absent.

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%, so baseline is 3, but the description adds real meaning: it explains why UNANSWERED is the recommended status and frames item_id as a narrowing filter. This goes beyond the schema's terse field docs.

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?

States a specific verb (List) and resource (pre-sale questions), plus scope (authenticated seller's listings, newest first). An agent can immediately distinguish this from the sibling answer_question, which the description explicitly links as the consumer of the returned ids.

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?

Explicitly names the primary use case (status='UNANSWERED' to find pending questions) and explains why it matters for conversion, and notes item_id restricts to one listing. It stops short of naming when not to use it or explicit alternatives beyond the implicit answer_question link.

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