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Mercado Libre MCP Server

Mercado Libre MCP Server

by MarcosNahuel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

get_reputation

Retrieves a Mercado Libre seller's reputation metrics—level, completed sales, claims, cancellations, and dispatch time—by seller ID.

Instructions

Obtiene la reputación de un vendedor: nivel, ventas completadas, reclamos, cancelaciones y tiempo de despacho.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "seller_id": "<seller_id>"
    },
    "name": "get_reputation"
  }
}

Input Schema

NameRequiredDescriptionDefault
seller_idYesID numérico del vendedor en ML

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.0-alpha.3

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full burden. It does disclose the substance of the response (level, completed sales, claims, cancellations, dispatch time), which is genuine behavioral context. However, it says nothing about permissions/scopes needed, whether it works for the authenticated seller only or any seller_id, error behavior for unknown IDs, or freshness of the reputation data.

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?

One sentence, front-loaded with the action and resource, followed by the most decision-relevant detail (what fields come back). Zero filler; every clause earns its place.

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 one-parameter read tool with no output schema, the description supplies what the structured fields cannot: the shape of the returned reputation data. The main gap is that with no annotations, read-only/non-destructive status is inferred from "Obtiene" rather than stated, and access scope is unaddressed.

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 100% with a single required seller_id already documented in-schema as "ID numérico del vendedor en ML". The description adds no format, range, or sourcing guidance beyond that, so the baseline of 3 applies — the schema does the work here.

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?

The description gives a specific verb and resource ("Obtiene la reputación de un vendedor") plus an enumeration of the reputation components returned: nivel, ventas completadas, reclamos, cancelaciones y tiempo de despacho. An agent can immediately tell this is the seller-reputation lookup, distinct from data-oriented siblings like get_orders or get_item_metrics. It stops short of explicitly naming a sibling it is not, which keeps it at 4.

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?

Usage is only implied: the description makes clear this is the tool for pulling a seller's reputation profile, so an agent evaluating a seller would infer it. There is no statement of when to prefer it over alternatives (e.g., get_orders for raw order data) and no prerequisites or exclusions noted.

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

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