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mercadolivre-mcp

mercadolivre-mcp

by matuck40
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Update item

ml_update_item
DestructiveIdempotent

Update fields of a Mercado Livre item, such as price, stock, or title. Preview the exact request first; changes apply only when confirm is true.

Instructions

Change fields of one of your Mercado Livre items (price, stock, title, status, pictures, variations, ...). Nothing is changed unless confirm=true. Call it without confirm first to get a preview (before, after and the exact request), show that preview to the user, and call again with confirm=true only after their explicit approval. Partial variations are completed with the ids of the item's other variations, because Mercado Livre deletes any variation missing from the request.

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": {
      "item_id": "<item_id>",
      "fields": "<fields>"
    },
    "name": "ml_update_item"
  }
}

Input Schema

NameRequiredDescriptionDefault
fieldsYesFields to change, sent as the PUT body, for example {"price": 59.9}.
confirmNofalse (default) returns a preview and changes nothing; true applies the change.
item_idYesItem id, for example MLB000000001.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare destructiveHint=true and idempotentHint=true, and the description goes well beyond them: it explains the dry-run/enact gate, specifies that the preview contains before, after, and the exact request, and warns that partial `variations` are auto-completed with the item's other variation ids because Mercado Livre deletes any variation missing from the request. That last point is exactly the kind of destructive side effect an agent needs and cannot infer from annotations.

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?

Three sentences, front-loaded with the purpose, then the safety gate, then the preview protocol, with the variations edge case last. Every sentence carries information that changes agent behavior; there is no filler.

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 destructive mutation tool with no output schema, the description supplies the missing pieces: what the dry-run returns, the approval requirement, and the variation-deletion hazard. Nothing essential for correct invocation is left unstated.

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 the baseline is 3. The description adds real meaning on two parameters: it defines what `confirm=false` returns (a preview with before/after/exact request) and clarifies the merge semantics of the nested `variations` object inside `fields`, which the schema does not cover. It does not document the full allowable field set, hence not a 5.

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 and resource ('Change fields of one of your Mercado Livre items') and enumerates the mutable field families (price, stock, title, status, pictures, variations), which cleanly separates it from read-oriented siblings like ml_get_item and ml_list_items. An agent can identify the tool's job without opening the schema.

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?

Gives an explicit two-phase protocol: call without confirm to get a preview, show it to the user, then re-call with confirm=true only after explicit approval. That is unusually clear 'when to use' guidance. It does not, however, route the agent to any sibling (e.g., ml_upload_picture for image assets), so it stops short of the full alternatives coverage a 5 requires.

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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